>>Hello everyone, This is Dave Lanta and you're watching The Cube's coverage of the Dell Technology Summit 2022 with exclusive behind the scenes interviews featuring Dell executive perspectives. And right now we're gonna explore Apex, which is Dell's as a service offering Dell's multi-cloud and edge strategies and the momentum around those. And we have news around Project Frontier, which is Dell's vision for its edge platform. And there's so much happening here. And don't forget, it's Cyber Security Awareness Month. Sam Groot is here. He's the senior vice president of marketing at Dell Technologies. Sam, always great to see you. How you doing? >>Always great to be here, Dave. >>All right, let's look at cloud. Everybody's talking about cloud Apex, multi-cloud. What's the update? How's it going? Where's the innovation and focal points of the strategy? >>Yeah, yeah. Look, Dave, if you think back over the course of this year, you've really heard us pivot as a company and discussing more and more about how multi-cloud is becoming a reality for our customers today. And when we listen and talk with our customers, they really describe multi-cloud challenges and a few key threads. One, the complexity is growing very, very quickly. Two, they're having a harder time controlling how their users are accessing the various different clouds. And then of course, finally the cloud costs are growing unchecked as well. So we, we like to describe this phenomenon as multi-cloud by design, where essentially organizations are waking up and seeing cloud sprawl around their organization every day. And this is creating more and more of those challenges. So of course at Dell we've got a strong point of view that you don't need to build multi-cloud by by default, rather it's multi-cloud by design, where you're very intentional in how you do multi-cloud. >>And how we deliver multi-cloud by design is through Apex. Apex is our modern cloud and our modern consumption experience. So when you think about the innovation as well, they've like, we've been on a pretty quick track record here in that, you know, the beginning of this year we introduced brand new Apex backup services that provides that SAS based backup service. We've introduced or announced Project Alpine, which is bringing our storage software, intellectual property from on-prem and putting it and running it natively in the public cloud. We've also introduced new Apex cyber recovery services that is simplifying how customers protect against cyber attacks. They can run an Amazon Azure, aw, I'm sorry, Amazon, aws, Azure or Google. And then, you know, we are really focused on this multi-cloud ecosystem. We announce key partnerships with SaaS providers such as Snowflake, where you can now access our information or our data from on-prem through the Snow Snowflake cloud. >>Or if needed, we can actually move the data to the Snowflake cloud if required. So we're continuing to build out that ecosystem SA providers. And then finally I would say, you know, we made a big strategic announcement just recently with Red Hat, where we're not only delivering new Apex container services, but we announce a strategic partnership to build jointly engineered solutions to address hybrid and multi-cloud solutions going forward. You know, VMware is gonna always continue to be a key partner of ours at the la at the recent VMware explorer, we announced new Tansu integration. So, So Dave, I, I think in a nutshell, we've been innovating at a very, very fast pace. We think there is a better way to do multi-cloud and that's multi-cloud by design. >>Yeah, we heard that at Dell Technologies world. First time I had heard that multi-cloud by design versus sort of default, which is great Alpine, which is sort of our, what we called super cloud in the making. And then of course the ecosystem is critical for any cloud company. VMware, of course, you know, top partner, but the Snowflake announcement was very interesting Red Hat. So seeing that expand, now let's go out to the edge. How's it going with the edge expansion? There's gotta be new. Speaking of ecosystem, the edge is like a whole different, you know, OT type That's right. Ecosystem's, telcos, what and what's this new frontier platform all about? >>Yeah, yeah. So we've talked a lot about clouds and multi clouds. We've talked about private and hybrid clouds, we've talked about public clouds, clouds and cos, telcos, et cetera. There's really been one key piece of our multi-cloud and technology strategy that we haven't spent a lot of time on. And that's the edge. And we do see that as that next frontier for our customers to really gain that competitive advantage that is created from their data and get closer to the point of creation where the data lives. And that's at the edge. We see the edge infrastructure space growing very, very quickly. We see upwards of 300% year of year growth in terms of amount of data being created at the edge. That's almost 3000 exabytes of data by 2026. So just incredible growth. And the edge is not really new for Dell. We've been at it for over 20 years of delivering edge solutions. >>81% of the Fortune 100 companies in the US use Dell solutions today at the Edge. And we are the number one OEM provider of Edge solutions with over 44,000 customers across over 40 industries and things like manufacturing, retail, edge healthcare, and more. So Dave, while we've been at it for a long time, we have such a, a deep understanding of how our customers are using Edge solutions. Say the bottom line is the game has gotta change. With that growth that we talked about, the new use cases that are emerging, we've got to un unlock this new frontier for customers to take advantage of the edge. And that's why we are announcing and revealing Project Frontier. And Project Frontier in its most simplest form, is a software platform that's gonna help customers and organizations really radically simplify their edge deployments by automating their edge operations. You know, with Project Frontier organizations are really gonna be able to manage, OP, and operate their edge infrastructure and application securely, efficiently and at scale. >>Okay, so it is, first of all, I like the name. It is software, it's a software architecture. So presumably a lot of API capabilities. That's right. Integration's. Is there hardware involved? >>Yeah, so of course you'll run it on Dell infrastructure. We'll be able to do both infrastructure, orchestration, orchestration through the platform, but as well as application orchestration. And you know, really there's, there's a handful of key drivers that have been really pushing our customers to take on and look at building a better way to do the edge with Project Frontier. And I think I would just highlight a handful of 'em. You know, freedom of choice. We definitely see this as an open ecosystem out there, even more so at the Edge than any other part of the IT stack. You know, being able to provide that freedom of choice for software applications or IOT frameworks, operational technology or OT for any of their edge use cases, that's really, really important. Another key area that we're helping to solve with Project Frontier is, you know, being able to expect zero trust security across all their edge applications from design to deployment, you know, and of course backed by an end and secure supply chain is really, really important to customers. >>And then getting that greater efficiency and reliability of operations with the centralized management through Project Frontier and Zero Touch deployments. You know, one of the biggest challenges, especially when you get out to the far, far reach of the frontier is really IT resources and being able to have that IT expertise. And we built in an enormous amount of automation helps streamline the edge deployments where you might be deploying a single edge solution, which is highly unlikely or hundreds or thousands, which is becoming more and more likely. So Dave, we do think Project Frontier is the right edge platform for customers to build their edge applications on now and certain, excuse me, certainly, and into the future. >>Yeah. Sam, no truck rolls. I like it. And you, you mentioned, you mentioned Zero trust, so we have Mother's Day, you, we have Father's Day. The kids always ask When's Kids' day? And we, of course we say every day is kids' day and every day should be cyber security awareness day. So, but we have cyber security awareness month. What does it mean for Dell? What are you hearing from customers and, and how are you responding? >>Yeah, yeah. No, there isn't a more prevalent top of mind conversation, whether it's the boardroom or the IT departments or every company is really have been forced to reckon with the cyber security and ransom secure issues out there. You know, every decision in IT department makes impacts your security profile. Those decisions can certainly, positively, hopefully impact it, but also can negatively impact it as well. So data security is, is really not a new area of focus for Dell. It's been an area that we've been focused on for a long time, but there are really three core elements to cybersecurity and data security as we go forward. The first is really setting the foundation of trust is really, really important across any IT system. And having the right supply chain in the right partner to partner with to deliver that is kind of the foundation in step one. >>Second, you need to of course go with technology that is trustworthy. It doesn't mean you are putting it together correctly. It means that you're essentially assembling the right piece parts together. That, that coexist together in the right way. You know, to truly change that landscape of the attackers out there that are gonna potentially create risk for your environment. We are definitely pushing and helping to embrace the zero trust principles and architectures that are out there. So finally, while when you think about security, it certainly is not absolute all correct. Security architectures assume that, you know, there are going to be challenges, there are going to be pain points, but you gotta be able to plan for recovery. And I think that's the holistic approach that we're taking with Dell. >>Well, and I think too, it's obviously security is a complicated situation now with cloud, you've got, you know, shared responsibility models, you've got that multi-cloud, you've got that across clouds, you're asking developers to do more. So I think the, the key takeaway is as a security pro, I'm looking for my technology partner through their r and d and their, you mentioned supply chain processes to take that off my plate so I can go plug holes elsewhere. Okay. Sam, put a bow on Dell Technology Summit for us and give us your closing thoughts. >>Yeah, look, I I think we're at a transformative point in it. You know, customers are moving more and more quickly to multi-cloud environments. They're looking to consume it in different ways, such as as a service, a lot of customers edge is new and an untapped opportunity for them to get closer to their customers and to their data. And of course there's more and more cyber threats out there every day. You know, our customers when we talk with them, they really want simple, consistent infrastructure options that are built on an open ecosystem that allows them to accomplish their goals quickly and successfully. And look, I think at Dell we've got the right strategy, we've got the right portfolio. We are the trusted partner of choice to help them lead, lead their, their future transformations into the future. So, Dave, look, I think it's, it's absolutely one of the most exciting times in it and I can't wait to see where it goes from here. >>Sam, always fun catching up with you. Appreciate your time. >>Thanks Dave. >>All right. A Dell Tech world in Vegas this past year, one of the most interesting conversations I personally had was around hybrid work and the future of work and the protocols associated with that and the mindset of, you know, the younger generation. And that conversation was, was with Jen Savira and we're gonna speak to Jen about this and other people and cult culture topics. Keep it right there. You're watching the Cube's exclusive coverage of Dell Technology Summit 2022.

>>As we said in our analysis of Dell's future, the transformation of Dell into Dell emc and now Dell Technologies has been one of the most remarkable stories in the history of the technology industry. After years of successfully integrated EMC and becoming VMware's number one distribution channel, the metamorphosis of Dell com culminated in the spin out of VMware from Dell and a massive wealth creation milestone pending, of course the Broadcom acquisition of VMware. So where's that leave Dell and what does the future look like for this technology powerhouse? Hello and welcome to the Cube's exclusive coverage of Dell Technology Summit 2022. My name is Dave Ante and I'll be hosting the program today In conjunction with the Dell Tech Summit. We'll hear from four of Dell's senior executives. Tom Sweet is the CFO of Dell Technologies. He's gonna share his views of the company's position and opportunities and answer the question, why is Dell good long term investment? >>Then we'll hear from Jeff Boudreau was the president of Dell's ISG business unit. He's gonna talk about the product angle and specifically how Dell is thinking about solving the multi-cloud challenge. And then Sam Grow Cot is the senior vice president of marketing's gonna come in the program and give us the update on Apex, which is Dell's as a service offering and a new edge platform called Project Frontier. By the way, it's also Cybersecurity Awareness Month, and we're gonna see if Sam has any stories there. And finally, for a company that's nearly 40 years old, Dell has some pretty forward thinking philosophies when it comes to its culture and workforce. And we're gonna speak with Jen Savira, who's Dell's chief Human Resource officer about hybrid work and how Dell is thinking about the future of work. We're gonna geek out all day and talk multi-cloud and edge and latency, but first, let's talk wallet. Tom Sweet cfo, and one of Dell's key business architects. Welcome back to the cube, >>Dave, it's good to see you and good to be back with you. So thanks for having me, Jay. >>Yeah, you bet. Tom. It's been a pretty incredible past 18 months. Not only the pandemic and all that craziness, but the VMware spin, you had to give up your gross margin binky as kidding, and, and of course the macro environment. I'm so sick of talking about the macro, but putting that aside for a moment, what's really remarkable is that for a company at your size, you've had some success at the top line, which I think surprised a lot of people. What are your reflections on the last 18 to 24 months? >>Well, Dave, it's been an incredible, not only last 18 months, but the whole transformation journey. If you think all the way back maybe to the LBO and forward from there, but, you know, stepping into the last 18 months, it's, you know, I, I think I remember talking with you and saying, Hey, you know, this scenario planning we did at the beginning of this pandemic journey was, you know, 30 different scenarios roughly, and none of which sort of panned out the way it actually did, which was a pretty incredible growth story as we think about how we helped customers, you know, drive workforce productivity, enabled their business model during the all remote work environment. That was the pandemic created. And couple that with the, you know, the, the rise then and the infrastructure spin as we got towards the tail end of the, of the pandemic coupled with, you know, the spin out of VMware, which culminated last November, as you know, as we completed that, which unlocked a pathway back to investment grade within unlocked, quite frankly shareholder value, capital allocation frameworks. It's really been a remarkable, you know, 18, 24 months. It's, it's never dull at Dell Technologies. Lemme put it that way. >>Well, well, I was impressed with you, Tom, before the leverage buyout and then what I've seen you guys navigate through is, is, is truly amazing. Well, let's talk about the challenging macro. I mean, I've been through a lot of downturns, but I've never seen anything quite like this with fed tightening and you're combating inflation, you got this recession looming, there's a bear market you got, but you got zero unemployment, you're rising wages, strong dollar, and it's very confusing. But it spending is, you know, it's somewhat softer, but it's still not bad. How are you seeing customers behave? How is Dell responding? >>Yeah, look, if you think about the markets we play in Dave, and we should start there as a grounding, you know, the, the total market, the core market that we think about is roughly 700 and, you know, 50 billion or so. If you think about our core IT services capability, you couple that with some of the, the growth initiatives that we're driving and the adjacent markets that that, that brings in, you're roughly talking a 1.4 to $1.5 trillion market opportunity, total addressable market. And so from from that perspective, we're extraordinarily bullish on where are we in the journey as we continue to grow and expand. You know, we have, we're number one share in just about every category that we plan, but yet when you look at that, you know, number one share in some of these, you know, our highest share position may be, you know, low thirties and maybe in the high end of storage you're at the upper end of thirties or 40%. >>But the opportunity there to continue to expand the core and, and continue to take share and outperform the market is truly extraordinary. So, so you step back and think about that, then you say, okay, what have we seen over the last number of months and quarters? It's been, you know, really great performance through the pandemic as, as you highlighted, we actually had a really strong first half of the year of our fiscal year 23 with revenue up 12% operating income up 12% for the first half. You know, what we talked about as you, if you might recall in our second quarter earnings, was the fact that we were starting to see softness. We had seen it in the consumer PC space, which is not a big area of focus for us in the sense of our, our total revenue stream, but we started to see commercial PC soften and we were starting to see server demand soften a bit and storage demand was, was holding quite frankly. >>And so we gave a a framework around guidance for the rest of the year as a, of what we were seeing. You know, the macro environment as you highlight it continues to be challenging. You know, if you look at inflation rates and the efforts by central banks across the globe to with through interest rate rise to press down and, and constrain growth and push down inflation, you couple that with supply chain challenges that continue principle, particularly in the ISG space. And then you couple that with the Ukraine war and the, and the energy crisis that that's created. And particularly in Europe, it's a pretty dynamic environment. And, but I'm confident, you know, I'm confident in the long term, but I do think that there is, you know, that there's navigation that we're going to have to do over the coming number of quarters, who knows quite how long, you know, to, to make sure the business is properly positioned and, you know, we've got a great portfolio and you're gonna talk to some of the team LA later on as you think your way through some of the solution capabilities we're driving what we're seeing around technology trends. >>So the opportunities there, there's some short term navigation that we're gonna need to do just to make sure that we address some of the, you know, some of the environmental things that we're seeing right >>Now. Yeah. And as a global company, of course you're converting local currencies back to appreciated dollars. That's, that's, that's another headwind. But as you say, I mean, that's math and you're navigating it. And again, I've seen a lot of downturns, but you know, the best companies not only weather the storm, but they invest in ways they that allow them to cut out, come out the other side stronger. So I wanna talk about that longer term opportunity, the relationship between the core, the the business growth. You mentioned the tam, I mean, even as a lower margin business, if, if you can penetrate that big of a tam, you could still throw off a lot of cash and you've got other levers to turn in potentially acquisitions and software. And, but so ultimately what gives you confidence in Dell's future? How should we think about Dell's future? >>Yeah, look, I, I think it comes down to we are extraordinarily excited about the opportunity over the long term digital transformation continues. I I am on numerous customer and CIO calls every week. Customers are continuing to invest in digital transformation and infrastructure to enable their business model. Yes, maybe it's gonna slow or, or pause or maybe they're not gonna invest quite at the same rate over the next number of quarters, but over the long term the needs are there. You look at what we're doing around the, the growth opportunities that we see, not only in our core space where we continue to invest, but also in the, what we call the strategic adjacencies. Things like 5G and modern telecom infrastructure as our, the telecom providers across the globe open up their, what a cl previous been closed ecosystems, you know, to open architecture. You think about, you know, what we're doing around the edge and the distribution now that we're seeing of compute and storage back to the edge given data gravity and latency matters. >>And so we're pretty bullish on the opportunity in front of us, you know, yes, we will and we're continuing to invest and you know, Jeff Boudreau talk about that I think later on in the program. So I'm excited about the opportunities and you look at our cash flow generation capability, you know, we are in, in, in normal times a, a cash flow generation machine and we'll continue to do so, You know, we've got a negative, you know, CCC in terms of, you know, how do we think about efficiency of working capital? And we look at our, you know, our capital allocation strategy, which has now returned, you know, somewhere in near 60% of our free cash flow back to shareholders. And so, you know, there's lots to, lots of reasons to think about why this, you know, we are a great sort of, I think value creation opportunity and a over the long term that the long term trends are with us, and I expect them to continue to be so, >>Yeah, and you guys, you, you, you do what you say you're gonna do. I mean, I said in my, in my other piece that I did recently, I think you guys put 46 billion on the, on the, on the balance sheet in terms of debt. That's down to I think 16 billion in the core, which that's quite remarking and that gives you some other opportunities. Give us your, your closing thoughts. I mean, you kind of just addressed why Dell is a good long term play, but I'll give you an opportunity to bring us home. >>Hey, Dave. Yeah, look, I, I just think if you look at the good, the market opportunity, the size and scale of Dell and how we think about the competitive advantages that we have, we com you know, if you look at, say we're a hundred billion revenue company, which we were a year, you know, last year, that as we reported roughly 60, 65 billion of that in the client, in in PC space, roughly, you know, 35 to 40 billion in the ISG or infrastructure space, those markets are gonna continue the opportunity to grow, share, grow at a premium to the market, drive, cash flow, drive, share gain is clearly there. You couple that with, you know, what we think the opportunity is in these adjacent markets, whether it's telecom, the edge, what we're thinking around data services, data management, you know, we, and you cut, you put that together with the long term trends around, you know, data creation and digital transformation. We are extraordinarily well positioned. We have the largest direct selling organization in in the technology space. We have the largest supply chain, our services footprint, you know, well positioned in my mind to take advantage of the opportunities as we move forward. >>Well Tom, really appreciate you taking the time to speak with us. Good to see you again. >>Nice seeing you. Thanks Dave. >>All right. You're watching the Cubes exclusive behind the scenes coverage of Dell Technology Summit 2022. In a moment, I'll be back with Jeff Boudreau. He's the president of Dell's ISG Infrastructure Solutions Group. He's responsible for all the important enterprise business at Dell, and we're excited to get his thoughts, keep it right there. >>Welcome back to the cube's exclusive coverage of the Dell Technology Summit. I'm Dave Ante and we're going inside with Dell execs to extract the signal from the noise. And right now we're gonna dig into customer requirements in a data intensive world and how cross cloud complexities get resolved from a product development perspective and how the ecosystem fits in to that mosaic to close the gaps and accelerate innovation. And with me now as friend of the cube, Jeff Boudreau, he's the president of the Infrastructure Solutions Group, ISG at Dell Technologies. Jeff, always good to see you. Welcome. >>You too. Thank you for having me. It's great to see you and thanks for having me back on the cube. I'm thrilled to be here. >>Yeah, it's our pleasure. Okay, so let's talk about what you're observing from customers today. You know, we talk all the time about operating in a data driven multi-cloud world, blah, blah, blah, blah. But what does that all mean to you when you have to translate that noise into products that solve specific customer problems, Jeff? >>Sure. Hey, great question. And everything always starts with our customers. There are motivation, they're top of mind, everything we do, my leadership team and I spend a lot of time with our customers. We're listening, we're learning, we're really understanding their pain points, and we wanna get their feedback in regards to our solutions, both turn and future offerings, really ensure that we're aligned to meeting their business objectives. I would say from these conversations, I'd say customers are telling us several things. First, it's all about data for no surprise going back to your opening. And second, it's about the multi-cloud world. And I'd say the big thing coming from all of this is that both of those are driving a ton of complexity for our customers. And I'll unpack that just a bit, which is first the data. As we all know, data is growing at unprecedented rates with more than 90% of the world's data being produced in the last two years alone. >>And you can just think of that in it's everywhere, right? And so as it as the IT world shifts towards distributed compute to support that data growth and that data gravity to really extract more value from that data in real time environments become inherently more and more hybrid and more and more multi-cloud. Which leads me to the second key point that I've been hearing from our customers, which it's a multi-cloud world, not new news. Customers by default have multiple clouds running across multiple locations that's on-prem and off-prem, it's running at the edge and it's serving a variety of different needs. Unfortunately, for most of our CU customers, multi-cloud is actually added to their complexity. As we've discussed. It's been a lot more of multi-cloud by default versus multi-cloud by design. And if you really think about our customers, I mean, I, I, I've talking to 'EM all the time, you think about the data complexity, that's the growth and the gravity. >>You think about their infrastructure complexity shifting from central to decentralized it, you think about multi-cloud complexity. So you have these walled gardens, if you will. So you have multiple vendors and you have these multiple contracts that all creates operational complexity for their teams around their processes of their tools. And then you think about security complexity that that dries with the, just the increased tax service and the list goes on. So what are we seeing for our customers? They, what they really want from us, and what they're asking us for is simplicity, not complexity. The immediacy, not latency. They're asking for open and aligned versus I'd say siloed and closed. And they're looking for a lot more agility and not rigidity in what we do. So they really wanna simplify everything. They're looking for a simpler IT and a more agile it. And they want more control of their data, right? >>And so, and they want to extract more of the value to enrich their business or their customer engagements, which all sounds pretty obvious and we've probably all heard it a bunch, but it's really hard to achieve. And that's where I believe, and we believe as Dell that we, it creates a big opportunity for us to really help our customers as that great simplifier of it. We're already doing this today on just a couple quick examples. First is Salesforce. We've supported recently, we've supported their global expansion with a multi-cloud solution to help them drive their business growth. Our solution delivered a reliable and consistent IT experience. We go back to that complexity and it was across a very distributed environment, including more than 60 data centers, 230 countries and hundreds of thousands of customers. It really provided Salesforce with the flexibility of placing workloads and data in an environment based on the right service level. >>Objective things like cost complexity or even security compliance considerations. The second customer A is a big New England Patriot fan. And Dan, Dave, I know you are as well. Oh yeah, this one's near, near data to my heart, it's the craft group. We just created a platform to span all the businesses that create more, I'd say data driven, immersive, secure experience, which is allowing them to capture data at the edge and use it for real time insights for things like cyber resiliency, but also like safety of the facilities. And as being a PA fan like I am, did they truly are meeting us where we are in our seats on their mobile devices and also in the parking lot. So just keep that in mind next time you're there. The bottom line, everything we're doing is really to make it simpler for our customers and to help them get the most of their data. I'd say we're gonna do this, is it through a multi-cloud by design approach, which we talked a lot about with you and and others at Dell Tech world earlier this year, >>Right? And we had Salesforce on, actually at Dell Tech group. The craft group is interesting because, you know, when you get to the stadium, you know, everybody's trying to get, get, get out to the internet and, and, but then the experience is so much better if you can actually, you know, deal with that edge. So I wanna talk about complexity though. You got data, you got, you know, the, the edge, you got multiple clouds, you got a different operating model across security model, different. So a lot of times in this industry we solve complexity with more complexity and it's like a bandaid. So I wanna, I wanna talk to, to how you're innovating around simplicity in ISG to address this complexity and what this means for Dell's long term strategy. >>Sure, I'd love to. So first I, I'd like to state the obvious, which are our investments in our innovations really focused on advancing, you know, our, our our customers needs, right? So we are really, our investments are gonna be targeted. We, we believe customers can have the most value. And some of that's gonna be around how we create strategic partnerships as well connected to what we just spoke about. Much of the complexity of customers have or experiencing is in the orchestration and management of all the data in all these different places and customers, you know, they must be able to quickly deploy and operate across cloud environments. They need to increase their developer productivity, really enabling those developers that do what they do best, which is creating more value for their customers than for their businesses. Our innovation efforts are really focused on addressing this by delivering an open and modern IT architecture that allows customers to run and manage any workload in any cloud anywhere. >>Data lives we're focused on, also focused on consumption based solutions, which allow for a greater degree of simplicity and flexibility, which they're really asking for as well. The foundation for this is our software to define common storage layer, that common storage layer. You can think about this Dave, as our ias if you will. It underpins our data access in mobility across all data types and locations. So you can think private, public, telecom, colo, edge, and it's delivered in a secure, holistic, and consistent cloud experience through Apex. We are making a ton of progress to let you just to be, just to be clear, we've made headway in things like Project Alpine, which you're very well aware of. This is our storage as a service. We announce this back in in January, which brings our unique software IP from our flagship storage platform to all the major public clouds. >>Really delivering the best of both worlds, allowing our customers to take advantage of Dell's enterprise class data services and storage software, such as performance at scale, resiliency, efficiency and security. But in addition to that, we're leveraging the breadth of the public cloud services, right? They're on demand scaling capabilities and access to analytical services. So in addition, we're really, we're, we're on our way to win at the edge as well with Project Frontier, which reduces complexity at the edge by creating an open and secure software platform to help our customers simplify their edge operations, optimize their edge environments and investments, secure that edge environment as well. I believe you're gonna be discussing Project Frontier here with Sam Gro Crop, the very near future. So I won't give up too many more details there. And lastly, we're also scaling Apex, which, oh, well, shifting from our vision, really shifting from vision to reality and introducing several new Apex service offerings, which are coming to market over the next month or so. And the intent is really supporting our customers on their as a service transitions by modernize the consumption experience and providing that flexible as a service model. Ultimately, we're trying to help our customers achieve that multi-cloud by design to really simplify it and unlock the power of their data. >>So some good examples there. I I like to talk about the super Cloud as you, you know, you're building on top of the, you know, hyperscale infrastructure and you got Apex is your cloud, the common storage layer, you call it your is. And that's, that's a ingredient in what we call the super cloud out to the edge. You have to have a common platform there and one of the hallmarks of a cloud company. And as you become a cloud company, everybody's a cloud company ecosystem becomes really, really important in terms of product development and, and innovation. Matt Baker always loves to stress it's not a zero zero sum game. And, and I think Super Cloud recognizes that, that there's value to be built on top of other clouds and, and, and of course on top of your infrastructure so that your ecosystem can add value. So what role does the ecosystem play there? >>For me, it's, it's pretty clear. It's, it's, it's critical. I can't say that enough above the having an open ecosystem. Think about everything we just discussed, and I agree with your super cloud analogy. I agree with what Matt Baker had said to you, I would certain no one company can actually address all the pain points and all the issues and challenges our customers are having on their own, not one. I think customers really want and deserve an open technology ecosystem, one that works together. So not these close stacks that discourages interoperability or stifles innovation and productivity of our, of each of our teams. We del I guess have a long history of supporting open ecosystems that really put customers first. And to be clear, we're gonna be at the center of the multi-cloud ecosystem and we're working with partners today to make that a reality. >>I mean, just think of what we're doing with VMware. We continue to build on our first and best alliances with them in August at their VMware explorer, which I know you were at, we announced several joint engineering initiatives to really help customers more easily manage and gain value from their data and their infrastructure. For multi-cloud specifically, we strength our relationship with VMware and with Tansu as part of that. In addition, just a few weeks ago we announced our partnership with Red Hat to simplify our multi-cloud deployments for managing containerized workloads. I'd say, and using your analogy, I could think of that as our multicloud platform. So that's kind of our PAs layer, if you will. And as you're aware, we have a very long standing and strategic partnership with Microsoft and I'd say stay tuned. There's a lot more to come with them and also others in this multicloud space. >>Shifting a bit to some of the growth engines that my team's responsible for the edge, right? As you think about data being everywhere, we've established partnerships for the Edge as well with folks like PTC and Litmus for the manufacturing edge, but also folks like Deep North for the retail edge analytics and data management. Using your Supercloud analogy, Dave the sa, right? This is our Sasa, we've announced that we're collaborating, partnering with folks like Snowflake and, and there's other data management companies as well to really simplify data access and accelerate those data insights. And then given customers choice of where they'd like to have their IT and their infrastructure, we've we're expanding our colo partnerships as well with folks like eex and, and they're allowing us to broaden our availability of Apex, providing customers the flexibility to take advantage of those as a service offerings wherever it's delivered and where they can get the most value. So those are just some you can hear from me. I think it's critical not only for, for us, I think it's critical for our customers. I think it's been critical, critical for the entire, you know, industry as a whole to really have that open technology ecosystem as we work with our customers on our multi-cloud solutions really to meet their needs. We'll continue to collaborate with whoever customers choose and you know, and who they want us to do business with. So I'd say a lot more coming in that space. >>So it's been an interesting three years for you, just, just over three years now since you've been made the president of the IS isg. And so you had to dig in and, and it was obviously a strange time around the world, but, but you really had to look at, okay, how do we modernize the platform? How do we make it, you know, cloud first, You've mentioned the edge, we're expanding. So what are the big takeaways? What do you want customers and our audience to understand? Just some closing thoughts and if you could summarize. >>Sure. So I'd say first, you know, we discussed we're working in a very fast paced, ever-changing market with massive amounts of data that needs to be managed. It's very complex and our customers need help with that complexity. I believe that Dell Technologies is uniquely positioned to help as their multicloud champion. No one else can solve the breadth and depth of the challenges like we can. And we're gonna help our customers move forward when they basically moving from a multi-cloud by default, as we've discussed before, to multicloud by design. And I'm really excited for the opportunity to work with our customers to help them expand that ecosystem as they truly realize the future of it and, and what they're trying to accomplish. >>Jeff, thanks so much. Really appreciate your time. Always a pleasure. Go pats and we'll see you on the blog. >>Thanks Dave. >>All right, you're watching exclusive insight insights from Dell Technology Summit on the cube, your leader in enterprise and emerging tech coverage. >>Hello everyone, this is Dave Lanta and you're watching the Cubes coverage of the Dell Technology Summit 2022 with exclusive behind the scenes interviews featuring Dell executive perspectives. And right now we're gonna explore Apex, which is Dell's as a service offering Dell's multi-cloud and edge strategies and the momentum around those. And we have news around Project Frontier, which is Dell's vision for its edge platform. And there's so much happening here. And don't forget it's cyber security Awareness month. Sam Grot is here, he's the senior vice president of marketing at Dell Technologies. Sam, always great to see you. How you doing? >>Always great to be here, Dave. >>All right, let's look at cloud. Everybody's talking about cloud Apex, multi-cloud, what's the update? How's it going? Where's the innovation and focal points of the strategy? >>Yeah, yeah. Look Dave, if you think back over the course of this year, you've really heard, heard us pivot as a company and discussing more and more about how multi-cloud is becoming a reality for our customers today. And when we listen and talk with our customers, they really describe multi-cloud challenges and a few key threads. One, the complexity is growing very, very quickly. Two, they're having a harder time controlling how their users are accessing the various different clouds. And then of course, finally the cloud costs are growing unchecked as well. So we, we like to describe this phenomenon as multi-cloud by design. We're essentially, organizations are waking up and seeing cloud sprawl around their organization every day. And this is creating more and more of those challenges. So of course at Dell we've got a strong point of view that you don't need to build multicloud by by default, rather it's multicloud by design where you're very intentional in how you do multicloud. >>And how we deliver multicloud by design is through apex. Apex is our modern cloud and our modern consumption experience. So when you think about the innovation as well, Dave, like we've been on a pretty quick track record here in that, you know, the beginning of this year we introduced brand new Apex backup services that provides that SAS based backup service. We've introduced or announced project outline, which is bringing our storage software, intellectual property from on-prem and putting it and running it natively in the public cloud. We've also introduced new Apex cyber recovery services that is simplifying how customers protect against cyber attacks. They can run an Amazon Azure, aw, I'm sorry, Amazon, aws, Azure or Google. And then, you know, we are really focused on this multi-cloud ecosystem. We announce key partnerships with SaaS providers such as Snowflake, where you can now access our information or our data from on-prem through the Snow Snowflake cloud. >>Or if needed, we can actually move the data to the Snowflake cloud if required. So we're continuing to build out that ecosystem SaaS providers. And then finally I would say, you know, we made a big strategic announcement just recently with Red Hat, where we're not only delivering new Apex container services, but we announce the strategic partnership to build jointly engineered solutions to address hybrid and multi-cloud solutions going forward. You know, VMware is gonna always continue to be a key partner of ours at the la at the recent VMware explorer we announced new Tansu integration. So, So Dave, I, I think in a nutshell we've been innovating at a very, very fast pace. We think there is a better way to do multi-cloud and that's multi-cloud by design. >>Yeah, we heard that at Dell Technologies world. First time I had heard that multi-cloud by design versus sort of default, which is great Alpine, which is sort of our, what we called super cloud in the making. And then of course the ecosystem is critical for any cloud company. VMware of course, you know, top partner, but the Snowflake announcement was very interesting Red Hat. So seeing that expand, now let's go out to the edge. How's it going with the edge expansion? There's gotta be new speaking of ecosystem, the edge is like a whole different, you know, OT type, that's right, ecosystem, that's telcos what and what's this new frontier platform all about? >>Yeah, yeah. So we've talked a lot about cloud and multi clouds, we've talked about private and hybrid cloud, we've talked about public clouds, clouds and cos, telcos, et cetera. There's really been one key piece of our multi-cloud and technology strategy that we haven't spent a lot of time on. And that's the edge. And we do see that as that next frontier for our customers to really gain that competitive advantage that is created from their data and get closer to the point of creation where the data lives. And that's at the edge. We see the edge infrastructure space growing very, very quickly. We see upwards of 300% year of year growth in terms of amount of data being created at the edge. That's almost 3000 exabytes of data by 2026. So just incredible growth. And the edge is not really new for Dell. We've been at it for over 20 years of delivering edge solutions. >>81% of the Fortune 100 companies in the US use Dell solutions today at the Edge. And we are the number one OEM provider of Edge solutions with over 44,000 customers across over 40 industries and things like manufacturing, retail, edge healthcare, and more. So Dave, while we've been at it for a long time, we have such a, a deep understanding of how our customers are using Edge solutions. Say the bottom line is the game has gotta change. With that growth that we talked about, the new use cases that are emerging, we've got to un unlock this new frontier for customers to take advantage of the edge. And that's why we are announcing and revealing Project Frontier. And Project Frontier in its most simplest form, is a software platform that's gonna help customers and organizations really radically simplify their edge deployments by automating their edge operations. You know, with Project Frontier organizations are really gonna be able to manage, OP, and operate their edge infrastructure and applications securely, efficiently and at scale. >>Okay, so it is, first of all, I like the name, it is software, it's a software architecture. So presumably a lot of API capabilities. That's right. Integration's. Is there hardware involved? >>Yeah, so of course you'll run it on Dell infrastructure. We'll be able to do both infrastructure orchestration, orchestration through the platform, but as well as application orchestration. And you know, really there's, there's a handful of key drivers that have been really pushing our customers to take on and look at building a better way to do the edge with Project Frontier. And I think I would just highlight a handful of 'em, you know, freedom of choice. We definitely see this as an open ecosystem out there, even more so at the Edge than any other part of the IT stack. You know, being able to provide that freedom of choice for software applications or I O T frameworks, operational technology or OT for any of their edge use cases, that's really, really important. Another key area that we're helping to solve with Project Frontier is, you know, being able to expect zero trust security across all their edge applications from design to deployment, you know, and of course backed by an end and secure supply chain is really, really important to customers. >>And then getting that greater efficiency and reliability of operations with the centralized management through Project Frontier and Zero Touch deployments. You know, one of the biggest challenges, especially when you get out to the far, far reach of the frontier is really IT resources and being able to have the IT expertise and we built in an enormous amount of automation helps streamline the edge deployments where you might be deploying a single edge solution, which is highly unlikely or hundreds or thousands, which is becoming more and more likely. So Dave, we do think Project Frontier is the right edge platform for customers to build their edge applications on now and certain, excuse me, certainly, and into the future. >>Yeah. Sam, no truck rolls. I like it. And you, you mentioned, you mentioned Zero trust. So we have Mother's Day, we have Father's Day. The kids always ask When's kids' day? And we of course we say every day is kids' day and every day should be cybersecurity awareness day. So, but we have cybersecurity awareness month. What does it mean for Dell? What are you hearing from customers and, and how are you responding? >>Yeah, yeah. No, there isn't a more prevalent pop of mind conversation, whether it's the boardroom or the IT departments or every company is really have been forced to reckon with the cybersecurity and ransom secure issues out there. You know, every decision in IT department makes impacts your security profile. Those decisions can certainly, positively, hopefully impact it, but also can negatively impact it as well. So data security is, is really not a new area of focus for Dell. It's been an area that we've been focused on for a long time, but there are really three core elements to cyber security and data security as we go forward. The first is really setting the foundation of trust is really, really important across any IT system. And having the right supply chain and the right partner to partner with to deliver that is kind of the foundation in step one. >>Second, you need to of course go with technology that is trustworthy. It doesn't mean you are putting it together correctly. It means that you're essentially assembling the right piece parts together. That, that coexist together in the right way. You know, to truly change that landscape of the attackers out there that are gonna potentially create risk for your environment. We are definitely pushing and helping to embrace the zero trust principles and architectures that are out there. So finally, while when you think about security, it certainly is not absolute all correct. Security architectures assume that, you know, there are going to be challenges, there are going to be pain points, but you've gotta be able to plan for recovery. And I think that's the holistic approach that we're taking with Dell. >>Well, and I think too, it's obviously security is a complicated situation now with cloud you've got, you know, shared responsibility models, you've got that a multi-cloud, you've got that across clouds, you're asking developers to do more. So I think the, the key takeaway is as a security pro, I'm looking for my technology partner through their r and d and their, you mentioned supply chain processes to take that off my plate so I can go plug holes elsewhere. Okay, Sam, put a bow on Dell Technology Summit for us and give us your closing thoughts. >>Yeah, look, I I think we're at a transformative point in it. You know, customers are moving more and more quickly to multi-cloud environments. They're looking to consume it in different ways, such as as a service, a lot of customers edge is new and an untapped opportunity for them to get closer to their customers and to their data. And of course there's more and more cyber threats out there every day. You know, our customers when we talk with them, they really want simple, consistent infrastructure options that are built on an open ecosystem that allows them to accomplish their goals quickly and successfully. And look, I think at Dell we've got the right strategy, we've got the right portfolio, we are the trusted partner of choice, help them lead, lead their, their future transformations into the future. So Dave, look, I think it's, it's absolutely one of the most exciting times in it and I can't wait to see where it goes from here. >>Sam, always fun catching up with you. Appreciate your time. >>Thanks Dave. >>All right. A Dell tech world in Vegas this past year, one of the most interesting conversations I personally had was around hybrid work and the future of work and the protocols associated with that and the mindset of, you know, the younger generation. And that conversation was with Jen Savira and we're gonna speak to Jen about this and other people and culture topics. Keep it right there. You're watching the cube's exclusive coverage of Dell Technology Summit 2022. Okay, we're back with Jen Vera, who's the chief human resource officer of Dell, and we're gonna discuss people, culture and hybrid work and leadership in the post isolation economy. Jen, the conversations that we had at Dell Tech World this past May around the new work environment were some of the most interesting and engaging that I had personally. So I'm really eager to, to get the update. It's great to see you again. Thanks for coming on the cube. >>Thanks for having me Dave. There's been a lot of change in just a short amount of time, so I'm excited to, to share some of our learnings >>With you. I, I mean, I bet there has, I mean, post pandemic companies, they're trying, everybody's trying to figure out the return to work and, and what it looks like. You know, last May there was really a theme of flexibility, but depending, we talked about, well, millennial or not young old, and it's just really was mixed, but, so how have you approached the topic? What, what are your policies? What's changed since we last talked? You know, what's working, you know, what's still being worked? What would you recommend to other companies to over to you? >>Yeah, well, you know, this isn't a topic that's necessarily new to Dell technology. So we've been doing hybrid before. Hybrid was a thing. So for over a decade we've been doing what we called connected workplace. So we have kind of a, a history and we have some great learnings from that. Although things did change for the entire world. You know, March of 2020, we went from kind of this hybrid to everybody being remote for a while. But what we wanted to do is, we're such a data driven company, there's so many headlines out there, you know, about all these things that people think could happen will happen, but there wasn't a lot of data behind it. So we took a step back and we asked our team members, How do you think we're doing? And we asked very kind of strong language because we've been doing this for a while. >>We asked them, Do you think we're leading in the world of hybrid in 86% of our team members said that we were, which is great, but we always know there's nuance right behind that macro level. So we, we asked 'em a lot of different questions and we just went on this kind of myth busting journey and we decided to test some of those things. We're hearing about Culture Willow Road or new team members will have trouble being connected or millennials will be different. And we really just collected a lot of data, asked our team members what their experience is. And what we have found is really, you don't have to be together in the office all the time to have a strong culture, a sense of connection, to be productive and to have it really healthy business. >>Well, I like that you were data driven around it in the data business here. So, but, but there is a lot of debate around your culture and how it suffers in a hybrid environment, how remote workers won't get, you know, promoted. And so I'm curious, you know, and I've, and I've seen some like-minded companies like Dell say, Hey, we, we want you guys to work the way you wanna work. But then they've, I've seen them adjust and say, Well yeah, but we also want you to know in the office be so we can collaborate a little bit more. So what are you seeing at Dell and, and, and how do you maintain that cultural advantage that you're alluding to in this kind of strange, new ever changing world? >>Yeah, well I think, look, one approach doesn't fit all. So I don't think that the approach that works for Dell Technologies isn't necessarily the approach that works for every company. It works with our strategy and culture. It is really important that we listen to our team members and that we support them through this journey. You know, they tell us time and time again, one of the most special things about our culture is that we provide flexibility and choice. So we're not a mandate culture. We really want to make sure that our team members know that we want them to be their best and do their best. And not every individual role has the same requirements. Not every individual person has the same needs. And so we really wanna meet them where they are so that they can be productive. They feel connected to the team and to the company and engaged and inspired. >>So, you know, for, for us, it really does make sense to go forward with this. And so we haven't, we haven't taken a step back. We've been doing hybrid, we'll continue to do hybrid, but just like if you, you know, we talk about not being a mandate. I think the companies that say nobody will come in or you have to come in three days a week, all of that feels more limiting. And so what we really say is, work out with your team, work out with your role, workout with your leader, what really makes the most sense to drive things forward. >>I >>You were, so >>That's what we, you were talking before about myths and you know, I wanna talk about team member performance cuz there's a lot of people believe that if, if you're not in the office, you have disadvantages, people in the office have the advantage cuz they get FaceTime. Is is that a myth? You know, is there some truth to that? What, what do you think about that? >>Well, for us, you know, we look, again, we just looked at the data. So we said we don't wanna create a have and have not culture that you're talking about. We really wanna have an inclusive culture. We wanna be outcome driven, we're meritocracy. But we went and we looked at the data. So pre pandemic, we looked at things like performance, we looked at rewards and recognition, we looked at attrition rates, we looked at sentiment, Do you feel like your leader is inspiring? And we found no meaningful differences in any of that or in engagement between those who worked fully remote, fully in the office or some combination between. So our data would bust that myth and say, it doesn't, you don't have to be in an office and be seen to get ahead. We have equitable opportunity. Now, having said that, you always have to be watching that data. And that's something that we'll continue to do and make sure that we are creating equal opportunity regardless of where you work. >>And it's personal too, I think, I think some people can be really productive at home. I happen to be one that I'm way more productive in the office cause the dogs aren't barking. I have less distractions. And so I think we think, and, and I think the takeaway that in just in talking to, to, to you Jen and, and folks at Dell is, you know, whatever works for you, we're we're gonna, we're gonna support. So I I wanted to switch gears a little bit, talk about leadership and, and very specifically empathic leadership has been said to be, have a big impact on attracting talent, retaining talent, but, but it's hard to have empathy sometimes. And I know I saw some stats in a recent Dell study. It was like two thirds the people felt like their organization underestimates the people requirements. And I, I ask myself, I'm like, what am I missing? I hope, you know, with our folks, so especially as it relates to, to transformation programs. So how can human resource practitioners support business leaders generally, specifically as it relates to leading with empathy? >>I think empathy's always been important. You have to develop trust. You can have the best strategy in the world, right? But if you don't feel like your leader understands who you are, appreciates the the value that you bring to the company, then you're not gonna get very far. So I think empathetic leadership has always been part of the foundation of a trusting, strong relationship between a leader and a team member. But if I think we look back on the last two years, and I imagine it'll be even more so as we go forward, empathetic leadership will be even more important. There's so much going on in the world, politically, socially, economically, that taking that time to say you want your team members to see you as credible, that you and confident that you can take us forward, but also that, you know, and understand me as a human being. >>And that to me is really what it's about. And I think with regard to transformation that you brought up, I think one of the things we forget about is leaders. We've probably been thinking about a decision or transformation for months or weeks and we're ready to go execute, we're ready to go operationalize that thing. And so sometimes when we get to that point, because we've been talking about it for so long, we send out the email, we have the all hands and we just say we're ready to go. But our team members haven't always been on that journey for those months that we have. And so I think that empathetic moment to say, Okay, not everybody is on a change curve where I am. Let's take a pause, let me put myself in their shoes and really think about how we bring everybody along. >>You know, Jen, in the spirit of myth busting, I mean I'm one of those people who felt like that a business is gonna have a hard time, harder time fostering this culture of collaboration and innovation post isolation economy as they, they could pre covid. But you know, I noticed there's a, there's an announcement today that came across my desk, I think it's from Newsweek. Yes. And, and it's the list of top hundred companies recognized for employee motivation satisfaction. And it was really interesting because you, you always see, oh, we're the top 10 or the top hundred, But this says as a survey of 1.4 million employees from companies ranging from 50 to 10,000 employees. And it recognizes the companies that put respect, caring, and appreciation for their employees at the center of their business model. And they doing so have earned the loyalty and respect of the people who work for them. >>Number one on the list is Dell sap. So congratulations SAP was number two. I mean, there really isn't any other tech company on there, certainly no large tech companies on there. So I always see these lists, they go, Yeah, okay, that's cool, top a hundred, whatever. But top one in, in, in an industry where there's only two in the top is, is pretty impressive. And how does that relate to fostering my earlier skepticism of a culture of collaboration? So first of all, congratulations, you know, how'd you do it? And how are you succeeding in, in this new world? >>Well thanks. It does feel great to be number one, but you know, it doesn't happen by accident. And I think while most companies have a, a culture and a spouse values, we have ours called the culture code. But it's really been very important to us that it's not just a poster on the wall or or words on paper. And so we embed our culture code into all of our HR practices, that whole ecosystem from recognition of rewards to performance evaluation, to interviewing, to development. We build it into everything. So it really reflects who we are and you experience it every day. And then to make sure that we're not, you know, fooling ourselves, we ask all of our employees, do you feel like the behaviors you see and the experience you have every day reflects the culture code? And 94% of our team members say that, in fact it does. So I think that that's really been kind of the secret to our success. If you, if you listen to Michael Dell, he'll always say, you know, the most special thing about Dell is our culture and our people. And that comes through being very thoughtful and deliberate to preserve and protect and continue to focus on our culture. >>Don't you think too that repetition and, well first of all, belief in that cultural philosophy is, is important. And then kind of repeating, like you said, Yeah, it's not just a poster in the wall, but I remember like, you know, when we're kids, your parents tell you, okay, power positive thinking, do one to others as others, you know, you have others do it to you. Don't make the say you're gonna do some dumb things but don't do the same dumb things twice and you sort of fluff it up. But then as you mature you say, Wow, actually those were, >>They might have had a >>Were instilled in me and now I'm bringing them forward and, you know, paying it forward. But, but so i, it, it, my, I guess my, my point is, and it's kind of a point observation, but I'll turn it into a question, is isn't isn't consistency and belief in your values really, really important? >>I couldn't agree with you more, right? I think that's one of those things that we talk about it all the time and as an HR professional, you know, it's not the HR people just talking about our culture, it's our business leaders, it's our ceo, it's our COOs ev, it's our partners. We share our culture code with our partners and our vendors and our suppliers and, and everybody, this is important. We say when you interact with anybody at Dell Technologies, you should expect that this is the experience that you're gonna get. And so it is something that we talk about that we embed in, into everything that we do. And I think it's, it's really important that you don't just think it's a one and done cuz that's not how things really, really work >>Well. And it's a culture of respect, you know, high performance, high expectations, accountability at having followed the company and worked with the company for many, many years. You always respect the dignity of your partners and your people. So really appreciate your time Jen. Again, congratulations on being number one. >>Thank you so much. >>You're very welcome. Okay. You've been watching a special presentation of the cube inside Dell Technology Summit 2022. Remember, these episodes are all available on demand@thecube.net and you can check out s silicon angle.com for all the news and analysis. And don't forget to check out wikibon.com each week for a new episode of breaking analysis. This is Dave Valante, thanks for watching and we'll see you next time.

>>Hi, we're back day two of Falcon, 2022. We're live from the area in Las Vegas, Silicon angles, the queue. My name is Dave Lanta and Rob Picard is here. He's the security lead for Vanta a company that CrowdStrike just made an investment in. Rob. Thanks for coming to the cube. >>Thank you very much. Happy to be here. So >>That's big news. You know, you got a, a big name, like CrowdStrike strategic investment. Tell us about that. >>Yeah, it's very exciting because CrowdStrike obviously is, you know, a major name in the security space and Vanta is a really leading the way in a lot of the compliance automation, but being able to sort of dip into that, that security space more and more having crowd strike behind us is huge. >>What is compliant? Compliance automation. Tell us more about what Vanta does. Yeah. >>So Vanta ultimately is a tool that gives you an automatic way to prepare for your SOC two audit or your ISO 27 0 1 audit or, you know, insert long list of dozens of standards we're working on here. But in the olden days you would provide a thousand screenshots to an auditor that proves that for the past year, past six months, you've been doing what you say you're doing, Banta just plugs directly into your systems and proves that evidence to them without the need for all of >>That. Okay. So software's a service and you yeah. Software charge monthly or okay. >>Yeah, something like that. >>Educate me if I'm cloud first or cloud only can't I just pull a SOC report off of AWS and send that to the auditors and say, here you go, >>That'll help. Right? Like if you, if you do that, if you're in AWS and you pull their, you know, I think their security hub, you can pull some of these controls in. Right. But the question is, what do you do then about your endpoints, right? What do you do about, Hey, did we off board everybody from all of the systems we have enabled, right? All of the SAS systems we use. And so what van does is we integrate with AWS, but we also integrate with every other system you're using, including your HR system and your identity provider, to make sure that, Hey, you know, all of these things are, are working in sync to ensure your compliance. So >>You're relatively new parent, but you ever, you know, the book, if you give a mouse, a cookie, you will, you will, the whole thing is you give a mouse, a cookie, and then 8 million things happen, all these other dependencies. And it goes around and around and around. Yes. He's gonna want some milk. Okay. I feel like it's the same thing in your world, right? I mean, there is, is, is there an end, when do you know you're done? >>Yeah. I mean, ultimately, you know, you're done when the O auditor hands you, your sock to report, you know, you have your at stage, you say, Hey, I'm sock too compliant. Or, you know, your ISO cert, but even then it's gonna keep going. Right. I think the tricky part is there are some key systems that you, you want to have, you know, your eyes on and you wanna be monitoring and making sure that Hey, in a year from now, when that audit happens, I'm not gonna be surprised at what they find. Right. And those are gonna be your cloud provider. Right. Those are gonna be your HR system telling you when people joined, when people left, and those are gonna be your identity provider and your endpoints, right. >>Are you guys obviously compliance experts? Is, is it really a matter of sort of codifying that expertise? Or is there a machine intelligence component involved, you know, discovery? How does it work? >>That's a great question, actually. And I think part of it is, you know, encoding that expertise in the product and making sure that, you know, there's not necessarily, you know, if you ask any given sock to auditor for like, Hey, what controls should I be using that you're gonna audit me against? And it's your job to come up with the control. So they'll provide you some, you know, their set, but it's gonna be different between them, right? The standard itself is not a list of controls, but what we can do is we can provide you that list of controls and say like, Hey, we've actually worked with a ton of auditors and they've worked with us and we can say, this is what you need to do to get started here. And then if you have custom controls to add later, you want you, you can do that. >>But so there's part of that's encoding the expertise, but then part of it is just understanding the world of, of the auditors enough that we can help guide you through it. Because, you know, like you said, you can go to AWS, you can get download a report, right. That says, look, I have, you know, these, so two controls past right now, but the question is, you know, you still have to then go hand that to an auditor, have conversations with them, get through all of their questions back to you. And that can get really, really in the weeds. So we have like teams of experts who sit on calls with auditors and customers and help them through this stuff when needed. Right. And hopefully it's not needed as much when you're, you know, automating most of it. So >>That's a, a component of your offering is, is a services capability. Is that part of the offering? Is that a for pay service? >>Yeah. So, you know, you have to talk to the sales team to understand how they bundle it all, but, you know, essentially we have these professional services teams and these partners that jump in, I think a lot of times it really is just, Hey, like the auditor asks this question. We don't know how to answer it. We'll send somebody to jump on, >>Let's jump on a call. Exactly. But if you need more intense, you >>Know, work services, then maybe that's available. Yeah. >>Okay. And, and is there a privacy aspect of your software? >>Yeah. So Vanta software does actually also support GDPR and CCPA to kind of help you. You know, it's hard to get your head around that stuff. You wanna talk about like encoding expertise, you know, having people inside Vanta who can talk through the product and say like, Hey, this is what we need to test for in a customer's environment. And this is what we need to point to that maybe, you know, you can't automatically test for, but we can give them some template policies or, or procedures for them to have in their company. And we can provide all of that to try to, to help you feel good about, Hey, we're, we're compliant with GDPR or we're compliant with CCPA and we're not gonna have problems here. And, >>And da is data, data sovereignty I presume is, is part of that. Like, >>You know, data sovereignty, man. I'm not the expert on data sovereignty. I'll tell you that. But I know that is definitely a part of that. I don't know, you know, how deep it goes when it comes to, you know, the requirements of any given company. >>Well, it's tricky because a lot of it hasn't been tested in the, in courts of law. That's just sort of guidelines there. Yeah. And then a lot of times you don't, how do you really know where the data is? Right. I mean, you kind of can infer it, but, >>And you can get real clever. You can start encrypting data that sits somewhere here, but you have the keys over here and say, no, no, no, the keys are in the right country. You know, that counts, >>Right. It gets real tricky. It's not really been tested that the logic of that, what are the hard parts of what you guys do and, and, and what makes you different from everybody else out there? >>Yeah. I mean, I think I'd say a couple things are, are really hard about what we do, right. One is maintaining good reputations with auditors because the goal is ultimately that an auditor sees Vanta and they say, okay, Vanta says that checkbox is checked. I don't have to worry about it. And that's where we are with so many auditors today. Right. But that wasn't like that in the beginning, in the beginning, it was, you know, Hey, we're showing you the code that actually looks and checks that box. Right. But the other hard part is just integrating with the long tail of systems that every customer needs, right? Like if you use a certain HR system and we don't support it, then that's gonna really dampen your value that you get outta the product. So the engineering challenges, maintaining a reliable set of both high quality tests and high quality integrations with these surfaces, >>What are the synergies with, with CrowdStrike kind of, you know, it's, maybe it seems obvious, but explain where you pick up and where they leave off. >>Yeah. I think that's a, that's a great point. So, you know, we have a very, like a very, a very simple agent that will run. If you need something on your laptop that says, Hey, look, this laptop, the disc is encrypted, right? The screen lock is set appropriately for my controls, right? So we have some, some basic capabilities it's based on OS query for, for those interested, but it's not a full fledged endpoint protection platform. Right. And that's where something like CrowdStrike can come in where we can integrate with them and say, okay, Hey, if you're ready to move on to something, that's, that's a little bit more full-fledged and a little bit more of a, you know, gonna protect you against malware and that sort of thing. Then you can move onto CrowdStrike and we can integrate directly with them and we can pull all the information we need and we can check all those boxes for you that say, Hey, you have appropriate malware protection, you have discs encrypted, you have whatever it may be. Right. We can pull that information from them. And we can also help you make sure that the people have access to CrowdStrike itself in your company are the right set of people. >>Who do you sell to, do you sell to the audit function within a company? Or do you sell directly to big auditors? Both. >>So it's, we're mainly selling to the whoever's responsible for getting that. So to getting that ISO, getting GDPR, you know, all these sorts of things at a company, right? So for a small business, right, a startup that's like two people could >>Be the developer >>Team. Exactly. We're selling either to the founders or developers or something like that. And we're saying, Hey, you don't wanna think about this at all. We can get you like 80% of the way there without having to send a single screenshot. And then there's like 20% of like, all right, we'll help you, you know, partner you with the right auditor. That's good for your company and, and get you over the line. But then as we go and we sell to a mid-market company, or, you know, even potentially an enterprise, we're talking to people who have very specific expertise in either security or compliance, who also don't wanna have to do all this manual work. >>And it's a pure SAS model. It runs in the cloud. How does it work? I just pointed at whatever software I want to, to, to, to get, you know, certified >>That's exactly right. It's, it's pure SAS. You go to, you know, the app do vanda.com. You log in and then you go to the integrations page, right. You're, you're starting fresh. And you say, okay, well, AWS, here's how you integrate AWS. Right? We use there assume role functionality and stuff like that to pull in, you know, read only data from AWS. And then you can also go to your Okta and you can say, okay, well, I can connect here through Okta, through, you know, an Okta app or I can connect to my Google through an oof that has the right permissions. So we try to just limit the amount of permissions we have or the scope of our, our, you know, roles. But really it's just, you know, it's all API based integrations that we then just pull the data. We need to prove that you're doing what you say you're doing all >>Well, Rob, congratulations on the funding and the activity here at, at CrowdStrike. Good show. So, you know, good luck to you in the future. >>Thank you very much. All right. >>You're very welcome. All right. Keep it right there, Dave. Valante for the cube. We'll be right back, but right after this strip break from Falcon 22, live from the area in Las Vegas,

>>In 2011, early Facebook employee and Cloudera co-founder Jeff Ocker famously said the best minds of my generation are thinking about how to get people to click on ads. And that sucks. Let's face it more than a decade later organizations continue to be frustrated with how difficult it is to get value from data and build a truly agile data-driven enterprise. What does that even mean? You ask? Well, it means that everyone in the organization has the data they need when they need it. In a context that's relevant to advance the mission of an organization. Now that could mean cutting cost could mean increasing profits, driving productivity, saving lives, accelerating drug discovery, making better diagnoses, solving, supply chain problems, predicting weather disasters, simplifying processes, and thousands of other examples where data can completely transform people's lives beyond manipulating internet users to behave a certain way. We've heard the prognostications about the possibilities of data before and in fairness we've made progress, but the hard truth is the original promises of master data management, enterprise data, warehouses, data marts, data hubs, and yes, even data lakes were broken and left us wanting from more welcome to the data doesn't lie, or doesn't a series of conversations produced by the cube and made possible by Starburst data. >>I'm your host, Dave Lanta and joining me today are three industry experts. Justin Borgman is this co-founder and CEO of Starburst. Richard Jarvis is the CTO at EMI health and Theresa tongue is cloud first technologist at Accenture. Today we're gonna have a candid discussion that will expose the unfulfilled and yes, broken promises of a data past we'll expose data lies, big lies, little lies, white lies, and hidden truths. And we'll challenge, age old data conventions and bust some data myths. We're debating questions like is the demise of a single source of truth. Inevitable will the data warehouse ever have featured parody with the data lake or vice versa is the so-called modern data stack, simply centralization in the cloud, AKA the old guards model in new cloud close. How can organizations rethink their data architectures and regimes to realize the true promises of data can and will and open ecosystem deliver on these promises in our lifetimes, we're spanning much of the Western world today. Richard is in the UK. Teresa is on the west coast and Justin is in Massachusetts with me. I'm in the cube studios about 30 miles outside of Boston folks. Welcome to the program. Thanks for coming on. Thanks for having us. Let's get right into it. You're very welcome. Now here's the first lie. The most effective data architecture is one that is centralized with a team of data specialists serving various lines of business. What do you think Justin? >>Yeah, definitely a lie. My first startup was a company called hit adapt, which was an early SQL engine for hit that was acquired by Teradata. And when I got to Teradata, of course, Teradata is the pioneer of that central enterprise data warehouse model. One of the things that I found fascinating was that not one of their customers had actually lived up to that vision of centralizing all of their data into one place. They all had data silos. They all had data in different systems. They had data on prem data in the cloud. You know, those companies were acquiring other companies and inheriting their data architecture. So, you know, despite being the industry leader for 40 years, not one of their customers truly had everything in one place. So I think definitely history has proven that to be a lie. >>So Richard, from a practitioner's point of view, you know, what, what are your thoughts? I mean, there, there's a lot of pressure to cut cost, keep things centralized, you know, serve the business as best as possible from that standpoint. What, what is your experience show? >>Yeah, I mean, I think I would echo Justin's experience really that we, as a business have grown up through acquisition, through storing data in different places sometimes to do information governance in different ways to store data in, in a platform that's close to data experts, people who really understand healthcare data from pharmacies or from, from doctors. And so, although if you were starting from a Greenfield site and you were building something brand new, you might be able to centralize all the data and all of the tooling and teams in one place. The reality is that that businesses just don't grow up like that. And, and it's just really impossible to get that academic perfection of, of storing everything in one place. >>Y you know, Theresa, I feel like Sarbanes Oxley kinda saved the data warehouse, you know, right. You actually did have to have a single version of the truth for certain financial data, but really for those, some of those other use cases, I, I mentioned, I, I do feel like the industry has kinda let us down. What's your take on this? Where does it make sense to have that sort of centralized approach versus where does it make sense to maybe decentralized? >>I, I think you gotta have centralized governance, right? So from the central team, for things like star Oxley, for things like security for certainly very core data sets, having a centralized set of roles, responsibilities to really QA, right. To serve as a design authority for your entire data estate, just like you might with security, but how it's implemented has to be distributed. Otherwise you're not gonna be able to scale. Right? So being able to have different parts of the business really make the right data investments for their needs. And then ultimately you're gonna collaborate with your partners. So partners that are not within the company, right. External partners, we're gonna see a lot more data sharing and model creation. And so you're definitely going to be decentralized. >>So, you know, Justin, you guys last, geez, I think it was about a year ago, had a session on, on data mesh. It was a great program. You invited Jamma, Dani, of course, she's the creator of the data mesh. And her one of our fundamental premises is that you've got this hyper specialized team that you've gotta go through. And if you want anything, but at the same time, these, these individuals actually become a bottleneck, even though they're some of the most talented people in the organization. So I guess question for you, Richard, how do you deal with that? Do you, do you organize so that there are a few sort of rock stars that, that, you know, build cubes and, and the like, and, and, and, or have you had any success in sort of decentralizing with, you know, your, your constituencies, that data model? >>Yeah. So, so we absolutely have got rockstar, data scientists and data guardians. If you like people who understand what it means to use this data, particularly as the data that we use at emos is very private it's healthcare information. And some of the, the rules and regulations around using the data are very complex and, and strict. So we have to have people who understand the usage of the data, then people who understand how to build models, how to process the data effectively. And you can think of them like consultants to the wider business, because a pharmacist might not understand how to structure a SQL query, but they do understand how they want to process medication information to improve patient lives. And so that becomes a, a consulting type experience from a, a set of rock stars to help a, a more decentralized business who needs to, to understand the data and to generate some valuable output. >>Justin, what do you say to a, to a customer or prospect that says, look, Justin, I'm gonna, I got a centralized team and that's the most cost effective way to serve the business. Otherwise I got, I got duplication. What do you say to that? >>Well, I, I would argue it's probably not the most cost effective and, and the reason being really twofold. I think, first of all, when you are deploying a enterprise data warehouse model, the, the data warehouse itself is very expensive, generally speaking. And so you're putting all of your most valuable data in the hands of one vendor who now has tremendous leverage over you, you know, for many, many years to come. I think that's the story at Oracle or Terra data or other proprietary database systems. But the other aspect I think is that the reality is those central data warehouse teams is as much as they are experts in the technology. They don't necessarily understand the data itself. And this is one of the core tenants of data mash that that jam writes about is this idea of the domain owners actually know the data the best. >>And so by, you know, not only acknowledging that data is generally decentralized and to your earlier point about SAR, brain Oxley, maybe saving the data warehouse, I would argue maybe GDPR and data sovereignty will destroy it because data has to be decentralized for, for those laws to be compliant. But I think the reality is, you know, the data mesh model basically says, data's decentralized, and we're gonna turn that into an asset rather than a liability. And we're gonna turn that into an asset by empowering the people that know the data, the best to participate in the process of, you know, curating and creating data products for, for consumption. So I think when you think about it, that way, you're going to get higher quality data and faster time to insight, which is ultimately going to drive more revenue for your business and reduce costs. So I think that that's the way I see the two, the two models comparing and contrasting. >>So do you think the demise of the data warehouse is inevitable? I mean, I mean, you know, there Theresa you work with a lot of clients, they're not just gonna rip and replace their existing infrastructure. Maybe they're gonna build on top of it, but what does that mean? Does that mean the E D w just becomes, you know, less and less valuable over time, or it's maybe just isolated to specific use cases. What's your take on that? >>Listen, I still would love all my data within a data warehouse would love it. Mastered would love it owned by essential team. Right? I think that's still what I would love to have. That's just not the reality, right? The investment to actually migrate and keep that up to date. I would say it's a losing battle. Like we've been trying to do it for a long time. Nobody has the budgets and then data changes, right? There's gonna be a new technology. That's gonna emerge that we're gonna wanna tap into. There's going to be not enough investment to bring all the legacy, but still very useful systems into that centralized view. So you keep the data warehouse. I think it's a very, very valuable, very high performance tool for what it's there for, but you could have this, you know, new mesh layer that still takes advantage of the things. I mentioned, the data products in the systems that are meaningful today and the data products that actually might span a number of systems, maybe either those that either source systems for the domains that know it best, or the consumer based systems and products that need to be packaged in a way that be really meaningful for that end user, right? Each of those are useful for a different part of the business and making sure that the mesh actually allows you to use all of them. >>So, Richard, let me ask you, you take, take Gemma's principles back to those. You got to, you know, domain ownership and, and, and data as product. Okay, great. Sounds good. But it creates what I would argue are two, you know, challenges, self-serve infrastructure let's park that for a second. And then in your industry, the one of the high, most regulated, most sensitive computational governance, how do you automate and ensure federated governance in that mesh model that Theresa was just talking about? >>Well, it absolutely depends on some of the tooling and processes that you put in place around those tools to be, to centralize the security and the governance of the data. And I think, although a data warehouse makes that very simple, cause it's a single tool, it's not impossible with some of the data mesh technologies that are available. And so what we've done at emus is we have a single security layer that sits on top of our data match, which means that no matter which user is accessing, which data source, we go through a well audited well understood security layer. That means that we know exactly who's got access to which data field, which data tables. And then everything that they do is, is audited in a very kind of standard way, regardless of the underlying data storage technology. So for me, although storing the data in one place might not be possible understanding where your source of truth is and securing that in a common way is still a valuable approach and you can do it without having to bring all that data into a single bucket so that it's all in one place. And, and so having done that and investing quite heavily in making that possible has paid dividends in terms of giving wider access to the platform and ensuring that only data that's available under GDPR and other regulations is being used by, by the data users. >>Yeah. So Justin, I mean, Democrat, we always talk about data democratization and you know, up until recently, they really haven't been line of sight as to how to get there. But do you have anything to add to this because you're essentially taking, you know, do an analytic queries and with data that's all dispersed all over the, how are you seeing your customers handle this, this challenge? >>Yeah. I mean, I think data products is a really interesting aspect of the answer to that. It allows you to, again, leverage the data domain owners, people know the data, the best to, to create, you know, data as a product ultimately to be consumed. And we try to represent that in our product as effectively a almost eCommerce like experience where you go and discover and look for the data products that have been created in your organization. And then you can start to consume them as, as you'd like. And so really trying to build on that notion of, you know, data democratization and self-service, and making it very easy to discover and, and start to use with whatever BI tool you, you may like, or even just running, you know, SQL queries yourself, >>Okay. G guys grab a sip of water. After this short break, we'll be back to debate whether proprietary or open platforms are the best path to the future of data excellence, keep it right there. >>Your company has more data than ever, and more people trying to understand it, but there's a problem. Your data is stored across multiple systems. It's hard to access and that delays analytics and ultimately decisions. The old method of moving all of your data into a single source of truth is slow and definitely not built for the volume of data we have today or where we are headed while your data engineers spent over half their time, moving data, your analysts and data scientists are left, waiting, feeling frustrated, unproductive, and unable to move the needle for your business. But what if you could spend less time moving or copying data? What if your data consumers could analyze all your data quickly? >>Starburst helps your teams run fast queries on any data source. We help you create a single point of access to your data, no matter where it's stored. And we support high concurrency, we solve for speed and scale, whether it's fast, SQL queries on your data lake or faster queries across multiple data sets, Starburst helps your teams run analytics anywhere you can't afford to wait for data to be available. Your team has questions that need answers. Now with Starburst, the wait is over. You'll have faster access to data with enterprise level security, easy connectivity, and 24 7 support from experts, organizations like Zolando Comcast and FINRA rely on Starburst to move their businesses forward. Contact our Trino experts to get started. >>We're back with Jess Borgman of Starburst and Richard Jarvis of EVAs health. Okay, we're gonna get to lie. Number two, and that is this an open source based platform cannot give you the performance and control that you can get with a proprietary system. Is that a lie? Justin, the enterprise data warehouse has been pretty dominant and has evolved and matured. Its stack has mature over the years. Why is it not the default platform for data? >>Yeah, well, I think that's become a lie over time. So I, I think, you know, if we go back 10 or 12 years ago with the advent of the first data lake really around Hudu, that probably was true that you couldn't get the performance that you needed to run fast, interactive, SQL queries in a data lake. Now a lot's changed in 10 or 12 years. I remember in the very early days, people would say, you you'll never get performance because you need to be column there. You need to store data in a column format. And then, you know, column formats we're introduced to, to data apes, you have Parque ORC file in aro that were created to ultimately deliver performance out of that. So, okay. We got, you know, largely over the performance hurdle, you know, more recently people will say, well, you don't have the ability to do updates and deletes like a traditional data warehouse. >>And now we've got the creation of new data formats, again like iceberg and Delta and Hodi that do allow for updates and delete. So I think the data lake has continued to mature. And I remember a, a quote from, you know, Kurt Monash many years ago where he said, you know, know it takes six or seven years to build a functional database. I think that's that's right. And now we've had almost a decade go by. So, you know, these technologies have matured to really deliver very, very close to the same level performance and functionality of, of cloud data warehouses. So I think the, the reality is that's become a line and now we have large giant hyperscale internet companies that, you know, don't have the traditional data warehouse at all. They do all of their analytics in a data lake. So I think we've, we've proven that it's very much possible today. >>Thank you for that. And so Richard, talk about your perspective as a practitioner in terms of what open brings you versus, I mean, look closed is it's open as a moving target. I remember Unix used to be open systems and so it's, it is an evolving, you know, spectrum, but, but from your perspective, what does open give you that you can't get from a proprietary system where you are fearful of in a proprietary system? >>I, I suppose for me open buys us the ability to be unsure about the future, because one thing that's always true about technology is it evolves in a, a direction, slightly different to what people expect. And what you don't want to end up is done is backed itself into a corner that then prevents it from innovating. So if you have chosen a technology and you've stored trillions of records in that technology and suddenly a new way of processing or machine learning comes out, you wanna be able to take advantage and your competitive edge might depend upon it. And so I suppose for us, we acknowledge that we don't have perfect vision of what the future might be. And so by backing open storage technologies, we can apply a number of different technologies to the processing of that data. And that gives us the ability to remain relevant, innovate on our data storage. And we have bought our way out of the, any performance concerns because we can use cloud scale infrastructure to scale up and scale down as we need. And so we don't have the concerns that we don't have enough hardware today to process what we want to do, want to achieve. We can just scale up when we need it and scale back down. So open source has really allowed us to maintain the being at the cutting edge. >>So Jess, let me play devil's advocate here a little bit, and I've talked to Shaak about this and you know, obviously her vision is there's an open source that, that the data meshes open source, an open source tooling, and it's not a proprietary, you know, you're not gonna buy a data mesh. You're gonna build it with, with open source toolings and, and vendors like you are gonna support it, but to come back to sort of today, you can get to market with a proprietary solution faster. I'm gonna make that statement. You tell me if it's a lie and then you can say, okay, we support Apache iceberg. We're gonna support open source tooling, take a company like VMware, not really in the data business, but how, the way they embraced Kubernetes and, and you know, every new open source thing that comes along, they say, we do that too. Why can't proprietary systems do that and be as effective? >>Yeah, well, I think at least with the, within the data landscape saying that you can access open data formats like iceberg or, or others is, is a bit dis disingenuous because really what you're selling to your customer is a certain degree of performance, a certain SLA, and you know, those cloud data warehouses that can reach beyond their own proprietary storage drop all the performance that they were able to provide. So it is, it reminds me kind of, of, again, going back 10 or 12 years ago when everybody had a connector to Haddo and that they thought that was the solution, right? But the reality was, you know, a connector was not the same as running workloads in Haddo back then. And I think similarly, you know, being able to connect to an external table that lives in an open data format, you know, you're, you're not going to give it the performance that your customers are accustomed to. And at the end of the day, they're always going to be predisposed. They're always going to be incentivized to get that data ingested into the data warehouse, cuz that's where they have control. And you know, the bottom line is the database industry has really been built around vendor lockin. I mean, from the start, how, how many people love Oracle today, but our customers, nonetheless, I think, you know, lockin is, is, is part of this industry. And I think that's really what we're trying to change with open data formats. >>Well, that's interesting reminded when I, you know, I see the, the gas price, the tees or gas price I, I drive up and then I say, oh, that's the cash price credit card. I gotta pay 20 cents more, but okay. But so the, the argument then, so let me, let me come back to you, Justin. So what's wrong with saying, Hey, we support open data formats, but yeah, you're gonna get better performance if you, if you keep it into our closed system, are you saying that long term that's gonna come back and bite you cuz you're gonna end up, you mentioned Oracle, you mentioned Teradata. Yeah. That's by, by implication, you're saying that's where snowflake customers are headed. >>Yeah, absolutely. I think this is a movie that, you know, we've all seen before. At least those of us who've been in the industry long enough to, to see this movie play over a couple times. So I do think that's the future. And I think, you know, I loved what Richard said. I actually wrote it down. Cause I thought it was an amazing quote. He said, it buys us the ability to be unsure of the future. Th that that pretty much says it all the, the future is unknowable and the reality is using open data formats. You remain interoperable with any technology you want to utilize. If you want to use spark to train a machine learning model and you want to use Starbust to query via sequel, that's totally cool. They can both work off the same exact, you know, data, data sets by contrast, if you're, you know, focused on a proprietary model, then you're kind of locked in again to that model. I think the same applies to data, sharing to data products, to a wide variety of, of aspects of the data landscape that a proprietary approach kind of closes you in and locks you in. >>So I, I would say this Richard, I'd love to get your thoughts on it. Cause I talked to a lot of Oracle customers, not as many te data customers, but, but a lot of Oracle customers and they, you know, they'll admit, yeah, you know, they're jamming us on price and the license cost they give, but we do get value out of it. And so my question to you, Richard, is, is do the, let's call it data warehouse systems or the proprietary systems. Are they gonna deliver a greater ROI sooner? And is that in allure of, of that customers, you know, are attracted to, or can open platforms deliver as fast in ROI? >>I think the answer to that is it can depend a bit. It depends on your businesses skillset. So we are lucky that we have a number of proprietary teams that work in databases that provide our operational data capability. And we have teams of analytics and big data experts who can work with open data sets and open data formats. And so for those different teams, they can get to an ROI more quickly with different technologies for the business though, we can't do better for our operational data stores than proprietary databases. Today we can back off very tight SLAs to them. We can demonstrate reliability from millions of hours of those databases being run at enterprise scale, but for an analytics workload where increasing our business is growing in that direction, we can't do better than open data formats with cloud-based data mesh type technologies. And so it's not a simple answer. That one will always be the right answer for our business. We definitely have times when proprietary databases provide a capability that we couldn't easily represent or replicate with open technologies. >>Yeah. Richard, stay with you. You mentioned, you know, you know, some things before that, that strike me, you know, the data brick snowflake, you know, thing is, oh, is a lot of fun for analysts like me. You've got data bricks coming at it. Richard, you mentioned you have a lot of rockstar, data engineers, data bricks coming at it from a data engineering heritage. You get snowflake coming at it from an analytics heritage. Those two worlds are, are colliding people like PJI Mohan said, you know what? I think it's actually harder to play in the data engineering. So I E it's easier to for data engineering world to go into the analytics world versus the reverse, but thinking about up and coming engineers and developers preparing for this future of data engineering and data analytics, how, how should they be thinking about the future? What, what's your advice to those young people? >>So I think I'd probably fall back on general programming skill sets. So the advice that I saw years ago was if you have open source technologies, the pythons and Javas on your CV, you commander 20% pay, hike over people who can only do proprietary programming languages. And I think that's true of data technologies as well. And from a business point of view, that makes sense. I'd rather spend the money that I save on proprietary licenses on better engineers, because they can provide more value to the business that can innovate us beyond our competitors. So I think I would my advice to people who are starting here or trying to build teams to capitalize on data assets is begin with open license, free capabilities, because they're very cheap to experiment with. And they generate a lot of interest from people who want to join you as a business. And you can make them very successful early, early doors with, with your analytics journey. >>It's interesting. Again, analysts like myself, we do a lot of TCO work and have over the last 20 plus years. And in world of Oracle, you know, normally it's the staff, that's the biggest nut in total cost of ownership, not an Oracle. It's the it's the license cost is by far the biggest component in the, in the blame pie. All right, Justin, help us close out this segment. We've been talking about this sort of data mesh open, closed snowflake data bricks. Where does Starburst sort of as this engine for the data lake data lake house, the data warehouse fit in this, in this world? >>Yeah. So our view on how the future ultimately unfolds is we think that data lakes will be a natural center of gravity for a lot of the reasons that we described open data formats, lowest total cost of ownership, because you get to choose the cheapest storage available to you. Maybe that's S3 or Azure data lake storage, or Google cloud storage, or maybe it's on-prem object storage that you bought at a, at a really good price. So ultimately storing a lot of data in a deal lake makes a lot of sense, but I think what makes our perspective unique is we still don't think you're gonna get everything there either. We think that basically centralization of all your data assets is just an impossible endeavor. And so you wanna be able to access data that lives outside of the lake as well. So we kind of think of the lake as maybe the biggest place by volume in terms of how much data you have, but to, to have comprehensive analytics and to truly understand your business and understand it holistically, you need to be able to go access other data sources as well. And so that's the role that we wanna play is to be a single point of access for our customers, provide the right level of fine grained access controls so that the right people have access to the right data and ultimately make it easy to discover and consume via, you know, the creation of data products as well. >>Great. Okay. Thanks guys. Right after this quick break, we're gonna be back to debate whether the cloud data model that we see emerging and the so-called modern data stack is really modern, or is it the same wine new bottle? When it comes to data architectures, you're watching the cube, the leader in enterprise and emerging tech coverage. >>Your data is capable of producing incredible results, but data consumers are often left in the dark without fast access to the data they need. Starers makes your data visible from wherever it lives. Your company is acquiring more data in more places, more rapidly than ever to rely solely on a data centralization strategy. Whether it's in a lake or a warehouse is unrealistic. A single source of truth approach is no longer viable, but disconnected data silos are often left untapped. We need a new approach. One that embraces distributed data. One that enables fast and secure access to any of your data from anywhere with Starburst, you'll have the fastest query engine for the data lake that allows you to connect and analyze your disparate data sources no matter where they live Starburst provides the foundational technology required for you to build towards the vision of a decentralized data mesh Starburst enterprise and Starburst galaxy offer enterprise ready, connectivity, interoperability, and security features for multiple regions, multiple clouds and everchanging global regulatory requirements. The data is yours. And with Starburst, you can perform analytics anywhere in light of your world. >>Okay. We're back with Justin Boardman. CEO of Starbust Richard Jarvis is the CTO of EMI health and Theresa tongue is the cloud first technologist from Accenture. We're on July number three. And that is the claim that today's modern data stack is actually modern. So I guess that's the lie it's it is it's is that it's not modern. Justin, what do you say? >>Yeah. I mean, I think new isn't modern, right? I think it's the, it's the new data stack. It's the cloud data stack, but that doesn't necessarily mean it's modern. I think a lot of the components actually are exactly the same as what we've had for 40 years, rather than Terra data. You have snowflake rather than Informatica you have five trend. So it's the same general stack, just, you know, a cloud version of it. And I think a lot of the challenges that it plagued us for 40 years still maintain. >>So lemme come back to you just, but okay. But, but there are differences, right? I mean, you can scale, you can throw resources at the problem. You can separate compute from storage. You really, you know, there's a lot of money being thrown at that by venture capitalists and snowflake, you mentioned it's competitors. So that's different. Is it not, is that not at least an aspect of, of modern dial it up, dial it down. So what, what do you say to that? >>Well, it, it is, it's certainly taking, you know, what the cloud offers and taking advantage of that, but it's important to note that the cloud data warehouses out there are really just separating their compute from their storage. So it's allowing them to scale up and down, but your data still stored in a proprietary format. You're still locked in. You still have to ingest the data to get it even prepared for analysis. So a lot of the same sort of structural constraints that exist with the old enterprise data warehouse model OnPrem still exist just yes, a little bit more elastic now because the cloud offers that. >>So Theresa, let me go to you cuz you have cloud first in your, in your, your title. So what's what say you to this conversation? >>Well, even the cloud providers are looking towards more of a cloud continuum, right? So the centralized cloud, as we know it, maybe data lake data warehouse in the central place, that's not even how the cloud providers are looking at it. They have news query services. Every provider has one that really expands those queries to be beyond a single location. And if we look at a lot of where our, the future goes, right, that that's gonna very much fall the same thing. There was gonna be more edge. There's gonna be more on premise because of data sovereignty, data gravity, because you're working with different parts of the business that have already made major cloud investments in different cloud providers. Right? So there's a lot of reasons why the modern, I guess, the next modern generation of the data staff needs to be much more federated. >>Okay. So Richard, how do you deal with this? You you've obviously got, you know, the technical debt, the existing infrastructure it's on the books. You don't wanna just throw it out. A lot of, lot of conversation about modernizing applications, which a lot of times is a, you know, a microservices layer on top of leg legacy apps. How do you think about the modern data stack? >>Well, I think probably the first thing to say is that the stack really has to include the processes and people around the data as well is all well and good changing the technology. But if you don't modernize how people use that technology, then you're not going to be able to, to scale because just cuz you can scale CPU and storage doesn't mean you can get more people to use your data, to generate you more, more value for the business. And so what we've been looking at is really changing in very much aligned to data products and, and data mesh. How do you enable more people to consume the service and have the stack respond in a way that keeps costs low? Because that's important for our customers consuming this data, but also allows people to occasionally run enormous queries and then tick along with smaller ones when required. And it's a good job we did because during COVID all of a sudden we had enormous pressures on our data platform to answer really important life threatening queries. And if we couldn't scale both our data stack and our teams, we wouldn't have been able to answer those as quickly as we had. So I think the stack needs to support a scalable business, not just the technology itself. >>Well thank you for that. So Justin let's, let's try to break down what the critical aspects are of the modern data stack. So you think about the past, you know, five, seven years cloud obviously has given a different pricing model. De-risked experimentation, you know that we talked about the ability to scale up scale down, but it's, I'm, I'm taking away that that's not enough based on what Richard just said. The modern data stack has to serve the business and enable the business to build data products. I, I buy that. I'm a big fan of the data mesh concepts, even though we're early days. So what are the critical aspects if you had to think about, you know, paying, maybe putting some guardrails and definitions around the modern data stack, what does that look like? What are some of the attributes and, and principles there >>Of, of how it should look like or, or how >>It's yeah. What it should be. >>Yeah. Yeah. Well, I think, you know, in, in Theresa mentioned this in, in a previous segment about the data warehouse is not necessarily going to disappear. It just becomes one node, one element of the overall data mesh. And I, I certainly agree with that. So by no means, are we suggesting that, you know, snowflake or Redshift or whatever cloud data warehouse you may be using is going to disappear, but it's, it's not going to become the end all be all. It's not the, the central single source of truth. And I think that's the paradigm shift that needs to occur. And I think it's also worth noting that those who were the early adopters of the modern data stack were primarily digital, native born in the cloud young companies who had the benefit of, of idealism. They had the benefit of it was starting with a clean slate that does not reflect the vast majority of enterprises. >>And even those companies, as they grow up mature out of that ideal state, they go buy a business. Now they've got something on another cloud provider that has a different data stack and they have to deal with that heterogeneity that is just change and change is a part of life. And so I think there is an element here that is almost philosophical. It's like, do you believe in an absolute ideal where I can just fit everything into one place or do I believe in reality? And I think the far more pragmatic approach is really what data mesh represents. So to answer your question directly, I think it's adding, you know, the ability to access data that lives outside of the data warehouse, maybe living in open data formats in a data lake or accessing operational systems as well. Maybe you want to directly access data that lives in an Oracle database or a Mongo database or, or what have you. So creating that flexibility to really Futureproof yourself from the inevitable change that you will, you won't encounter over time. >>So thank you. So there, based on what Justin just said, I, my takeaway there is it's inclusive, whether it's a data Mar data hub, data lake data warehouse, it's a, just a node on the mesh. Okay. I get that. Does that include there on Preem data? O obviously it has to, what are you seeing in terms of the ability to, to take that data mesh concept on Preem? I mean, most implementations I've seen in data mesh, frankly really aren't, you know, adhering to the philosophy. They're maybe, maybe it's data lake and maybe it's using glue. You look at what JPMC is doing. Hello, fresh, a lot of stuff happening on the AWS cloud in that, you know, closed stack, if you will. What's the answer to that Theresa? >>I mean, I, I think it's a killer case for data. Me, the fact that you have valuable data sources, OnPrem, and then yet you still wanna modernize and take the best of cloud cloud is still, like we mentioned, there's a lot of great reasons for it around the economics and the way ability to tap into the innovation that the cloud providers are giving around data and AI architecture. It's an easy button. So the mesh allows you to have the best of both worlds. You can start using the data products on-prem or in the existing systems that are working already. It's meaningful for the business. At the same time, you can modernize the ones that make business sense because it needs better performance. It needs, you know, something that is, is cheaper or, or maybe just tap into better analytics to get better insights, right? So you're gonna be able to stretch and really have the best of both worlds. That, again, going back to Richard's point, that is meaningful by the business. Not everything has to have that one size fits all set a tool. >>Okay. Thank you. So Richard, you know, talking about data as product, wonder if we could give us your perspectives here, what are the advantages of treating data as a product? What, what role do data products have in the modern data stack? We talk about monetizing data. What are your thoughts on data products? >>So for us, one of the most important data products that we've been creating is taking data that is healthcare data across a wide variety of different settings. So information about patients' demographics about their, their treatment, about their medications and so on, and taking that into a standards format that can be utilized by a wide variety of different researchers because misinterpreting that data or having the data not presented in the way that the user is expecting means that you generate the wrong insight. And in any business, that's clearly not a desirable outcome, but when that insight is so critical, as it might be in healthcare or some security settings, you really have to have gone to the trouble of understanding the data, presenting it in a format that everyone can clearly agree on. And then letting people consume in a very structured, managed way, even if that data comes from a variety of different sources in, in, in the first place. And so our data product journey has really begun by standardizing data across a number of different silos through the data mesh. So we can present out both internally and through the right governance externally to, to researchers. >>So that data product through whatever APIs is, is accessible, it's discoverable, but it's obviously gotta be governed as well. You mentioned you, you appropriately provided to internally. Yeah. But also, you know, external folks as well. So the, so you've, you've architected that capability today >>We have, and because the data is standard, it can generate value much more quickly and we can be sure of the security and, and, and value that that's providing because the data product isn't just about formatting the data into the correct tables, it's understanding what it means to redact the data or to remove certain rows from it or to interpret what a date actually means. Is it the start of the contract or the start of the treatment or the date of birth of a patient? These things can be lost in the data storage without having the proper product management around the data to say in a very clear business context, what does this data mean? And what does it mean to process this data for a particular use case? >>Yeah, it makes sense. It's got the context. If the, if the domains own the data, you, you gotta cut through a lot of the, the, the centralized teams, the technical teams that, that data agnostic, they don't really have that context. All right. Let's send Justin, how does Starburst fit into this modern data stack? Bring us home. >>Yeah. So I think for us, it's really providing our customers with, you know, the flexibility to operate and analyze data that lives in a wide variety of different systems. Ultimately giving them that optionality, you know, and optionality provides the ability to reduce costs, store more in a data lake rather than data warehouse. It provides the ability for the fastest time to insight to access the data directly where it lives. And ultimately with this concept of data products that we've now, you know, incorporated into our offering as well, you can really create and, and curate, you know, data as a product to be shared and consumed. So we're trying to help enable the data mesh, you know, model and make that an appropriate compliment to, you know, the, the, the modern data stack that people have today. >>Excellent. Hey, I wanna thank Justin Theresa and Richard for joining us today. You guys are great. I big believers in the, in the data mesh concept, and I think, you know, we're seeing the future of data architecture. So thank you. Now, remember, all these conversations are gonna be available on the cube.net for on-demand viewing. You can also go to starburst.io. They have some great content on the website and they host some really thought provoking interviews and, and, and they have awesome resources, lots of data mesh conversations over there, and really good stuff in, in the resource section. So check that out. Thanks for watching the data doesn't lie or does it made possible by Starburst data? This is Dave Valante for the cube, and we'll see you next time. >>The explosion of data sources has forced organizations to modernize their systems and architecture and come to terms with one size does not fit all for data management today. Your teams are constantly moving and copying data, which requires time management. And in some cases, double paying for compute resources. Instead, what if you could access all your data anywhere using the BI tools and SQL skills your users already have. And what if this also included enterprise security and fast performance with Starburst enterprise, you can provide your data consumers with a single point of secure access to all of your data, no matter where it lives with features like strict, fine grained, access control, end to end data encryption and data masking Starburst meets the security standards of the largest companies. Starburst enterprise can easily be deployed anywhere and managed with insights where data teams holistically view their clusters operation and query execution. So they can reach meaningful business decisions faster, all this with the support of the largest team of Trino experts in the world, delivering fully tested stable releases and available to support you 24 7 to unlock the value in all of your data. You need a solution that easily fits with what you have today and can adapt to your architecture. Tomorrow. 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>>In 2011, early Facebook employee and Cloudera co-founder Jeff Ocker famously said the best minds of my generation are thinking about how to get people to click on ads. And that sucks. Let's face it more than a decade later organizations continue to be frustrated with how difficult it is to get value from data and build a truly agile data-driven enterprise. What does that even mean? You ask? Well, it means that everyone in the organization has the data they need when they need it. In a context that's relevant to advance the mission of an organization. Now that could mean cutting cost could mean increasing profits, driving productivity, saving lives, accelerating drug discovery, making better diagnoses, solving, supply chain problems, predicting weather disasters, simplifying processes, and thousands of other examples where data can completely transform people's lives beyond manipulating internet users to behave a certain way. We've heard the prognostications about the possibilities of data before and in fairness we've made progress, but the hard truth is the original promises of master data management, enterprise data, warehouses, data marts, data hubs, and yes, even data lakes were broken and left us wanting from more welcome to the data doesn't lie, or doesn't a series of conversations produced by the cube and made possible by Starburst data. >>I'm your host, Dave Lanta and joining me today are three industry experts. Justin Borgman is this co-founder and CEO of Starburst. Richard Jarvis is the CTO at EMI health and Theresa tongue is cloud first technologist at Accenture. Today we're gonna have a candid discussion that will expose the unfulfilled and yes, broken promises of a data past we'll expose data lies, big lies, little lies, white lies, and hidden truths. And we'll challenge, age old data conventions and bust some data myths. We're debating questions like is the demise of a single source of truth. Inevitable will the data warehouse ever have featured parody with the data lake or vice versa is the so-called modern data stack, simply centralization in the cloud, AKA the old guards model in new cloud close. How can organizations rethink their data architectures and regimes to realize the true promises of data can and will and open ecosystem deliver on these promises in our lifetimes, we're spanning much of the Western world today. Richard is in the UK. Teresa is on the west coast and Justin is in Massachusetts with me. I'm in the cube studios about 30 miles outside of Boston folks. Welcome to the program. Thanks for coming on. Thanks for having us. Let's get right into it. You're very welcome. Now here's the first lie. The most effective data architecture is one that is centralized with a team of data specialists serving various lines of business. What do you think Justin? >>Yeah, definitely a lie. My first startup was a company called hit adapt, which was an early SQL engine for hit that was acquired by Teradata. And when I got to Teradata, of course, Teradata is the pioneer of that central enterprise data warehouse model. One of the things that I found fascinating was that not one of their customers had actually lived up to that vision of centralizing all of their data into one place. They all had data silos. They all had data in different systems. They had data on prem data in the cloud. You know, those companies were acquiring other companies and inheriting their data architecture. So, you know, despite being the industry leader for 40 years, not one of their customers truly had everything in one place. So I think definitely history has proven that to be a lie. >>So Richard, from a practitioner's point of view, you know, what, what are your thoughts? I mean, there, there's a lot of pressure to cut cost, keep things centralized, you know, serve the business as best as possible from that standpoint. What, what is your experience show? >>Yeah, I mean, I think I would echo Justin's experience really that we, as a business have grown up through acquisition, through storing data in different places sometimes to do information governance in different ways to store data in, in a platform that's close to data experts, people who really understand healthcare data from pharmacies or from, from doctors. And so, although if you were starting from a Greenfield site and you were building something brand new, you might be able to centralize all the data and all of the tooling and teams in one place. The reality is that that businesses just don't grow up like that. And, and it's just really impossible to get that academic perfection of, of storing everything in one place. >>Y you know, Theresa, I feel like Sarbanes Oxley kinda saved the data warehouse, you know, right. You actually did have to have a single version of the truth for certain financial data, but really for those, some of those other use cases, I, I mentioned, I, I do feel like the industry has kinda let us down. What's your take on this? Where does it make sense to have that sort of centralized approach versus where does it make sense to maybe decentralized? >>I, I think you gotta have centralized governance, right? So from the central team, for things like star Oxley, for things like security for certainly very core data sets, having a centralized set of roles, responsibilities to really QA, right. To serve as a design authority for your entire data estate, just like you might with security, but how it's implemented has to be distributed. Otherwise you're not gonna be able to scale. Right? So being able to have different parts of the business really make the right data investments for their needs. And then ultimately you're gonna collaborate with your partners. So partners that are not within the company, right. External partners, we're gonna see a lot more data sharing and model creation. And so you're definitely going to be decentralized. >>So, you know, Justin, you guys last, geez, I think it was about a year ago, had a session on, on data mesh. It was a great program. You invited Jamma, Dani, of course, she's the creator of the data mesh. And her one of our fundamental premises is that you've got this hyper specialized team that you've gotta go through. And if you want anything, but at the same time, these, these individuals actually become a bottleneck, even though they're some of the most talented people in the organization. So I guess question for you, Richard, how do you deal with that? Do you, do you organize so that there are a few sort of rock stars that, that, you know, build cubes and, and the like, and, and, and, or have you had any success in sort of decentralizing with, you know, your, your constituencies, that data model? >>Yeah. So, so we absolutely have got rockstar, data scientists and data guardians. If you like people who understand what it means to use this data, particularly as the data that we use at emos is very private it's healthcare information. And some of the, the rules and regulations around using the data are very complex and, and strict. So we have to have people who understand the usage of the data, then people who understand how to build models, how to process the data effectively. And you can think of them like consultants to the wider business, because a pharmacist might not understand how to structure a SQL query, but they do understand how they want to process medication information to improve patient lives. And so that becomes a, a consulting type experience from a, a set of rock stars to help a, a more decentralized business who needs to, to understand the data and to generate some valuable output. >>Justin, what do you say to a, to a customer or prospect that says, look, Justin, I'm gonna, I got a centralized team and that's the most cost effective way to serve the business. Otherwise I got, I got duplication. What do you say to that? >>Well, I, I would argue it's probably not the most cost effective and, and the reason being really twofold. I think, first of all, when you are deploying a enterprise data warehouse model, the, the data warehouse itself is very expensive, generally speaking. And so you're putting all of your most valuable data in the hands of one vendor who now has tremendous leverage over you, you know, for many, many years to come. I think that's the story at Oracle or Terra data or other proprietary database systems. But the other aspect I think is that the reality is those central data warehouse teams is as much as they are experts in the technology. They don't necessarily understand the data itself. And this is one of the core tenants of data mash that that jam writes about is this idea of the domain owners actually know the data the best. >>And so by, you know, not only acknowledging that data is generally decentralized and to your earlier point about SAR, brain Oxley, maybe saving the data warehouse, I would argue maybe GDPR and data sovereignty will destroy it because data has to be decentralized for, for those laws to be compliant. But I think the reality is, you know, the data mesh model basically says, data's decentralized, and we're gonna turn that into an asset rather than a liability. And we're gonna turn that into an asset by empowering the people that know the data, the best to participate in the process of, you know, curating and creating data products for, for consumption. So I think when you think about it, that way, you're going to get higher quality data and faster time to insight, which is ultimately going to drive more revenue for your business and reduce costs. So I think that that's the way I see the two, the two models comparing and contrasting. >>So do you think the demise of the data warehouse is inevitable? I mean, I mean, you know, there Theresa you work with a lot of clients, they're not just gonna rip and replace their existing infrastructure. Maybe they're gonna build on top of it, but what does that mean? Does that mean the E D w just becomes, you know, less and less valuable over time, or it's maybe just isolated to specific use cases. What's your take on that? >>Listen, I still would love all my data within a data warehouse would love it. Mastered would love it owned by essential team. Right? I think that's still what I would love to have. That's just not the reality, right? The investment to actually migrate and keep that up to date. I would say it's a losing battle. Like we've been trying to do it for a long time. Nobody has the budgets and then data changes, right? There's gonna be a new technology. That's gonna emerge that we're gonna wanna tap into. There's going to be not enough investment to bring all the legacy, but still very useful systems into that centralized view. So you keep the data warehouse. I think it's a very, very valuable, very high performance tool for what it's there for, but you could have this, you know, new mesh layer that still takes advantage of the things. I mentioned, the data products in the systems that are meaningful today and the data products that actually might span a number of systems, maybe either those that either source systems for the domains that know it best, or the consumer based systems and products that need to be packaged in a way that be really meaningful for that end user, right? Each of those are useful for a different part of the business and making sure that the mesh actually allows you to use all of them. >>So, Richard, let me ask you, you take, take Gemma's principles back to those. You got to, you know, domain ownership and, and, and data as product. Okay, great. Sounds good. But it creates what I would argue are two, you know, challenges, self-serve infrastructure let's park that for a second. And then in your industry, the one of the high, most regulated, most sensitive computational governance, how do you automate and ensure federated governance in that mesh model that Theresa was just talking about? >>Well, it absolutely depends on some of the tooling and processes that you put in place around those tools to be, to centralize the security and the governance of the data. And I think, although a data warehouse makes that very simple, cause it's a single tool, it's not impossible with some of the data mesh technologies that are available. And so what we've done at emus is we have a single security layer that sits on top of our data match, which means that no matter which user is accessing, which data source, we go through a well audited well understood security layer. That means that we know exactly who's got access to which data field, which data tables. And then everything that they do is, is audited in a very kind of standard way, regardless of the underlying data storage technology. So for me, although storing the data in one place might not be possible understanding where your source of truth is and securing that in a common way is still a valuable approach and you can do it without having to bring all that data into a single bucket so that it's all in one place. And, and so having done that and investing quite heavily in making that possible has paid dividends in terms of giving wider access to the platform and ensuring that only data that's available under GDPR and other regulations is being used by, by the data users. >>Yeah. So Justin, I mean, Democrat, we always talk about data democratization and you know, up until recently, they really haven't been line of sight as to how to get there. But do you have anything to add to this because you're essentially taking, you know, do an analytic queries and with data that's all dispersed all over the, how are you seeing your customers handle this, this challenge? >>Yeah. I mean, I think data products is a really interesting aspect of the answer to that. It allows you to, again, leverage the data domain owners, people know the data, the best to, to create, you know, data as a product ultimately to be consumed. And we try to represent that in our product as effectively a almost eCommerce like experience where you go and discover and look for the data products that have been created in your organization. And then you can start to consume them as, as you'd like. And so really trying to build on that notion of, you know, data democratization and self-service, and making it very easy to discover and, and start to use with whatever BI tool you, you may like, or even just running, you know, SQL queries yourself, >>Okay. G guys grab a sip of water. After this short break, we'll be back to debate whether proprietary or open platforms are the best path to the future of data excellence, keep it right there. >>Your company has more data than ever, and more people trying to understand it, but there's a problem. Your data is stored across multiple systems. It's hard to access and that delays analytics and ultimately decisions. The old method of moving all of your data into a single source of truth is slow and definitely not built for the volume of data we have today or where we are headed while your data engineers spent over half their time, moving data, your analysts and data scientists are left, waiting, feeling frustrated, unproductive, and unable to move the needle for your business. But what if you could spend less time moving or copying data? What if your data consumers could analyze all your data quickly? >>Starburst helps your teams run fast queries on any data source. We help you create a single point of access to your data, no matter where it's stored. And we support high concurrency, we solve for speed and scale, whether it's fast, SQL queries on your data lake or faster queries across multiple data sets, Starburst helps your teams run analytics anywhere you can't afford to wait for data to be available. Your team has questions that need answers. Now with Starburst, the wait is over. You'll have faster access to data with enterprise level security, easy connectivity, and 24 7 support from experts, organizations like Zolando Comcast and FINRA rely on Starburst to move their businesses forward. Contact our Trino experts to get started. >>We're back with Jess Borgman of Starburst and Richard Jarvis of EVAs health. Okay, we're gonna get to lie. Number two, and that is this an open source based platform cannot give you the performance and control that you can get with a proprietary system. Is that a lie? Justin, the enterprise data warehouse has been pretty dominant and has evolved and matured. Its stack has mature over the years. Why is it not the default platform for data? >>Yeah, well, I think that's become a lie over time. So I, I think, you know, if we go back 10 or 12 years ago with the advent of the first data lake really around Hudu, that probably was true that you couldn't get the performance that you needed to run fast, interactive, SQL queries in a data lake. Now a lot's changed in 10 or 12 years. I remember in the very early days, people would say, you you'll never get performance because you need to be column there. You need to store data in a column format. And then, you know, column formats we're introduced to, to data apes, you have Parque ORC file in aro that were created to ultimately deliver performance out of that. So, okay. We got, you know, largely over the performance hurdle, you know, more recently people will say, well, you don't have the ability to do updates and deletes like a traditional data warehouse. >>And now we've got the creation of new data formats, again like iceberg and Delta and Hodi that do allow for updates and delete. So I think the data lake has continued to mature. And I remember a, a quote from, you know, Kurt Monash many years ago where he said, you know, know it takes six or seven years to build a functional database. I think that's that's right. And now we've had almost a decade go by. So, you know, these technologies have matured to really deliver very, very close to the same level performance and functionality of, of cloud data warehouses. So I think the, the reality is that's become a line and now we have large giant hyperscale internet companies that, you know, don't have the traditional data warehouse at all. They do all of their analytics in a data lake. So I think we've, we've proven that it's very much possible today. >>Thank you for that. And so Richard, talk about your perspective as a practitioner in terms of what open brings you versus, I mean, look closed is it's open as a moving target. I remember Unix used to be open systems and so it's, it is an evolving, you know, spectrum, but, but from your perspective, what does open give you that you can't get from a proprietary system where you are fearful of in a proprietary system? >>I, I suppose for me open buys us the ability to be unsure about the future, because one thing that's always true about technology is it evolves in a, a direction, slightly different to what people expect. And what you don't want to end up is done is backed itself into a corner that then prevents it from innovating. So if you have chosen a technology and you've stored trillions of records in that technology and suddenly a new way of processing or machine learning comes out, you wanna be able to take advantage and your competitive edge might depend upon it. And so I suppose for us, we acknowledge that we don't have perfect vision of what the future might be. And so by backing open storage technologies, we can apply a number of different technologies to the processing of that data. And that gives us the ability to remain relevant, innovate on our data storage. And we have bought our way out of the, any performance concerns because we can use cloud scale infrastructure to scale up and scale down as we need. And so we don't have the concerns that we don't have enough hardware today to process what we want to do, want to achieve. We can just scale up when we need it and scale back down. So open source has really allowed us to maintain the being at the cutting edge. >>So Jess, let me play devil's advocate here a little bit, and I've talked to Shaak about this and you know, obviously her vision is there's an open source that, that the data meshes open source, an open source tooling, and it's not a proprietary, you know, you're not gonna buy a data mesh. You're gonna build it with, with open source toolings and, and vendors like you are gonna support it, but to come back to sort of today, you can get to market with a proprietary solution faster. I'm gonna make that statement. You tell me if it's a lie and then you can say, okay, we support Apache iceberg. We're gonna support open source tooling, take a company like VMware, not really in the data business, but how, the way they embraced Kubernetes and, and you know, every new open source thing that comes along, they say, we do that too. Why can't proprietary systems do that and be as effective? >>Yeah, well, I think at least with the, within the data landscape saying that you can access open data formats like iceberg or, or others is, is a bit dis disingenuous because really what you're selling to your customer is a certain degree of performance, a certain SLA, and you know, those cloud data warehouses that can reach beyond their own proprietary storage drop all the performance that they were able to provide. So it is, it reminds me kind of, of, again, going back 10 or 12 years ago when everybody had a connector to Haddo and that they thought that was the solution, right? But the reality was, you know, a connector was not the same as running workloads in Haddo back then. And I think similarly, you know, being able to connect to an external table that lives in an open data format, you know, you're, you're not going to give it the performance that your customers are accustomed to. And at the end of the day, they're always going to be predisposed. They're always going to be incentivized to get that data ingested into the data warehouse, cuz that's where they have control. And you know, the bottom line is the database industry has really been built around vendor lockin. I mean, from the start, how, how many people love Oracle today, but our customers, nonetheless, I think, you know, lockin is, is, is part of this industry. And I think that's really what we're trying to change with open data formats. >>Well, that's interesting reminded when I, you know, I see the, the gas price, the tees or gas price I, I drive up and then I say, oh, that's the cash price credit card. I gotta pay 20 cents more, but okay. But so the, the argument then, so let me, let me come back to you, Justin. So what's wrong with saying, Hey, we support open data formats, but yeah, you're gonna get better performance if you, if you keep it into our closed system, are you saying that long term that's gonna come back and bite you cuz you're gonna end up, you mentioned Oracle, you mentioned Teradata. Yeah. That's by, by implication, you're saying that's where snowflake customers are headed. >>Yeah, absolutely. I think this is a movie that, you know, we've all seen before. At least those of us who've been in the industry long enough to, to see this movie play over a couple times. So I do think that's the future. And I think, you know, I loved what Richard said. I actually wrote it down. Cause I thought it was an amazing quote. He said, it buys us the ability to be unsure of the future. Th that that pretty much says it all the, the future is unknowable and the reality is using open data formats. You remain interoperable with any technology you want to utilize. If you want to use spark to train a machine learning model and you want to use Starbust to query via sequel, that's totally cool. They can both work off the same exact, you know, data, data sets by contrast, if you're, you know, focused on a proprietary model, then you're kind of locked in again to that model. I think the same applies to data, sharing to data products, to a wide variety of, of aspects of the data landscape that a proprietary approach kind of closes you in and locks you in. >>So I, I would say this Richard, I'd love to get your thoughts on it. Cause I talked to a lot of Oracle customers, not as many te data customers, but, but a lot of Oracle customers and they, you know, they'll admit, yeah, you know, they're jamming us on price and the license cost they give, but we do get value out of it. And so my question to you, Richard, is, is do the, let's call it data warehouse systems or the proprietary systems. Are they gonna deliver a greater ROI sooner? And is that in allure of, of that customers, you know, are attracted to, or can open platforms deliver as fast in ROI? >>I think the answer to that is it can depend a bit. It depends on your businesses skillset. So we are lucky that we have a number of proprietary teams that work in databases that provide our operational data capability. And we have teams of analytics and big data experts who can work with open data sets and open data formats. And so for those different teams, they can get to an ROI more quickly with different technologies for the business though, we can't do better for our operational data stores than proprietary databases. Today we can back off very tight SLAs to them. We can demonstrate reliability from millions of hours of those databases being run at enterprise scale, but for an analytics workload where increasing our business is growing in that direction, we can't do better than open data formats with cloud-based data mesh type technologies. And so it's not a simple answer. That one will always be the right answer for our business. We definitely have times when proprietary databases provide a capability that we couldn't easily represent or replicate with open technologies. >>Yeah. Richard, stay with you. You mentioned, you know, you know, some things before that, that strike me, you know, the data brick snowflake, you know, thing is, oh, is a lot of fun for analysts like me. You've got data bricks coming at it. Richard, you mentioned you have a lot of rockstar, data engineers, data bricks coming at it from a data engineering heritage. You get snowflake coming at it from an analytics heritage. Those two worlds are, are colliding people like PJI Mohan said, you know what? I think it's actually harder to play in the data engineering. So I E it's easier to for data engineering world to go into the analytics world versus the reverse, but thinking about up and coming engineers and developers preparing for this future of data engineering and data analytics, how, how should they be thinking about the future? What, what's your advice to those young people? >>So I think I'd probably fall back on general programming skill sets. So the advice that I saw years ago was if you have open source technologies, the pythons and Javas on your CV, you commander 20% pay, hike over people who can only do proprietary programming languages. And I think that's true of data technologies as well. And from a business point of view, that makes sense. I'd rather spend the money that I save on proprietary licenses on better engineers, because they can provide more value to the business that can innovate us beyond our competitors. So I think I would my advice to people who are starting here or trying to build teams to capitalize on data assets is begin with open license, free capabilities, because they're very cheap to experiment with. And they generate a lot of interest from people who want to join you as a business. And you can make them very successful early, early doors with, with your analytics journey. >>It's interesting. Again, analysts like myself, we do a lot of TCO work and have over the last 20 plus years. And in world of Oracle, you know, normally it's the staff, that's the biggest nut in total cost of ownership, not an Oracle. It's the it's the license cost is by far the biggest component in the, in the blame pie. All right, Justin, help us close out this segment. We've been talking about this sort of data mesh open, closed snowflake data bricks. Where does Starburst sort of as this engine for the data lake data lake house, the data warehouse fit in this, in this world? >>Yeah. So our view on how the future ultimately unfolds is we think that data lakes will be a natural center of gravity for a lot of the reasons that we described open data formats, lowest total cost of ownership, because you get to choose the cheapest storage available to you. Maybe that's S3 or Azure data lake storage, or Google cloud storage, or maybe it's on-prem object storage that you bought at a, at a really good price. So ultimately storing a lot of data in a deal lake makes a lot of sense, but I think what makes our perspective unique is we still don't think you're gonna get everything there either. We think that basically centralization of all your data assets is just an impossible endeavor. And so you wanna be able to access data that lives outside of the lake as well. So we kind of think of the lake as maybe the biggest place by volume in terms of how much data you have, but to, to have comprehensive analytics and to truly understand your business and understand it holistically, you need to be able to go access other data sources as well. And so that's the role that we wanna play is to be a single point of access for our customers, provide the right level of fine grained access controls so that the right people have access to the right data and ultimately make it easy to discover and consume via, you know, the creation of data products as well. >>Great. Okay. Thanks guys. Right after this quick break, we're gonna be back to debate whether the cloud data model that we see emerging and the so-called modern data stack is really modern, or is it the same wine new bottle? When it comes to data architectures, you're watching the cube, the leader in enterprise and emerging tech coverage. >>Your data is capable of producing incredible results, but data consumers are often left in the dark without fast access to the data they need. Starers makes your data visible from wherever it lives. Your company is acquiring more data in more places, more rapidly than ever to rely solely on a data centralization strategy. Whether it's in a lake or a warehouse is unrealistic. A single source of truth approach is no longer viable, but disconnected data silos are often left untapped. We need a new approach. One that embraces distributed data. One that enables fast and secure access to any of your data from anywhere with Starburst, you'll have the fastest query engine for the data lake that allows you to connect and analyze your disparate data sources no matter where they live Starburst provides the foundational technology required for you to build towards the vision of a decentralized data mesh Starburst enterprise and Starburst galaxy offer enterprise ready, connectivity, interoperability, and security features for multiple regions, multiple clouds and everchanging global regulatory requirements. The data is yours. And with Starburst, you can perform analytics anywhere in light of your world. >>Okay. We're back with Justin Boardman. CEO of Starbust Richard Jarvis is the CTO of EMI health and Theresa tongue is the cloud first technologist from Accenture. We're on July number three. And that is the claim that today's modern data stack is actually modern. So I guess that's the lie it's it is it's is that it's not modern. Justin, what do you say? >>Yeah. I mean, I think new isn't modern, right? I think it's the, it's the new data stack. It's the cloud data stack, but that doesn't necessarily mean it's modern. I think a lot of the components actually are exactly the same as what we've had for 40 years, rather than Terra data. You have snowflake rather than Informatica you have five trend. So it's the same general stack, just, you know, a cloud version of it. And I think a lot of the challenges that it plagued us for 40 years still maintain. >>So lemme come back to you just, but okay. But, but there are differences, right? I mean, you can scale, you can throw resources at the problem. You can separate compute from storage. You really, you know, there's a lot of money being thrown at that by venture capitalists and snowflake, you mentioned it's competitors. So that's different. Is it not, is that not at least an aspect of, of modern dial it up, dial it down. So what, what do you say to that? >>Well, it, it is, it's certainly taking, you know, what the cloud offers and taking advantage of that, but it's important to note that the cloud data warehouses out there are really just separating their compute from their storage. So it's allowing them to scale up and down, but your data still stored in a proprietary format. You're still locked in. You still have to ingest the data to get it even prepared for analysis. So a lot of the same sort of structural constraints that exist with the old enterprise data warehouse model OnPrem still exist just yes, a little bit more elastic now because the cloud offers that. >>So Theresa, let me go to you cuz you have cloud first in your, in your, your title. So what's what say you to this conversation? >>Well, even the cloud providers are looking towards more of a cloud continuum, right? So the centralized cloud, as we know it, maybe data lake data warehouse in the central place, that's not even how the cloud providers are looking at it. They have news query services. Every provider has one that really expands those queries to be beyond a single location. And if we look at a lot of where our, the future goes, right, that that's gonna very much fall the same thing. There was gonna be more edge. There's gonna be more on premise because of data sovereignty, data gravity, because you're working with different parts of the business that have already made major cloud investments in different cloud providers. Right? So there's a lot of reasons why the modern, I guess, the next modern generation of the data staff needs to be much more federated. >>Okay. So Richard, how do you deal with this? You you've obviously got, you know, the technical debt, the existing infrastructure it's on the books. You don't wanna just throw it out. A lot of, lot of conversation about modernizing applications, which a lot of times is a, you know, a microservices layer on top of leg legacy apps. How do you think about the modern data stack? >>Well, I think probably the first thing to say is that the stack really has to include the processes and people around the data as well is all well and good changing the technology. But if you don't modernize how people use that technology, then you're not going to be able to, to scale because just cuz you can scale CPU and storage doesn't mean you can get more people to use your data, to generate you more, more value for the business. And so what we've been looking at is really changing in very much aligned to data products and, and data mesh. How do you enable more people to consume the service and have the stack respond in a way that keeps costs low? Because that's important for our customers consuming this data, but also allows people to occasionally run enormous queries and then tick along with smaller ones when required. And it's a good job we did because during COVID all of a sudden we had enormous pressures on our data platform to answer really important life threatening queries. And if we couldn't scale both our data stack and our teams, we wouldn't have been able to answer those as quickly as we had. So I think the stack needs to support a scalable business, not just the technology itself. >>Well thank you for that. So Justin let's, let's try to break down what the critical aspects are of the modern data stack. So you think about the past, you know, five, seven years cloud obviously has given a different pricing model. De-risked experimentation, you know that we talked about the ability to scale up scale down, but it's, I'm, I'm taking away that that's not enough based on what Richard just said. The modern data stack has to serve the business and enable the business to build data products. I, I buy that. I'm a big fan of the data mesh concepts, even though we're early days. So what are the critical aspects if you had to think about, you know, paying, maybe putting some guardrails and definitions around the modern data stack, what does that look like? What are some of the attributes and, and principles there >>Of, of how it should look like or, or how >>It's yeah. What it should be. >>Yeah. Yeah. Well, I think, you know, in, in Theresa mentioned this in, in a previous segment about the data warehouse is not necessarily going to disappear. It just becomes one node, one element of the overall data mesh. And I, I certainly agree with that. So by no means, are we suggesting that, you know, snowflake or Redshift or whatever cloud data warehouse you may be using is going to disappear, but it's, it's not going to become the end all be all. It's not the, the central single source of truth. And I think that's the paradigm shift that needs to occur. And I think it's also worth noting that those who were the early adopters of the modern data stack were primarily digital, native born in the cloud young companies who had the benefit of, of idealism. They had the benefit of it was starting with a clean slate that does not reflect the vast majority of enterprises. >>And even those companies, as they grow up mature out of that ideal state, they go buy a business. Now they've got something on another cloud provider that has a different data stack and they have to deal with that heterogeneity that is just change and change is a part of life. And so I think there is an element here that is almost philosophical. It's like, do you believe in an absolute ideal where I can just fit everything into one place or do I believe in reality? And I think the far more pragmatic approach is really what data mesh represents. So to answer your question directly, I think it's adding, you know, the ability to access data that lives outside of the data warehouse, maybe living in open data formats in a data lake or accessing operational systems as well. Maybe you want to directly access data that lives in an Oracle database or a Mongo database or, or what have you. So creating that flexibility to really Futureproof yourself from the inevitable change that you will, you won't encounter over time. >>So thank you. So there, based on what Justin just said, I, my takeaway there is it's inclusive, whether it's a data Mar data hub, data lake data warehouse, it's a, just a node on the mesh. Okay. I get that. Does that include there on Preem data? O obviously it has to, what are you seeing in terms of the ability to, to take that data mesh concept on Preem? I mean, most implementations I've seen in data mesh, frankly really aren't, you know, adhering to the philosophy. They're maybe, maybe it's data lake and maybe it's using glue. You look at what JPMC is doing. Hello, fresh, a lot of stuff happening on the AWS cloud in that, you know, closed stack, if you will. What's the answer to that Theresa? >>I mean, I, I think it's a killer case for data. Me, the fact that you have valuable data sources, OnPrem, and then yet you still wanna modernize and take the best of cloud cloud is still, like we mentioned, there's a lot of great reasons for it around the economics and the way ability to tap into the innovation that the cloud providers are giving around data and AI architecture. It's an easy button. So the mesh allows you to have the best of both worlds. You can start using the data products on-prem or in the existing systems that are working already. It's meaningful for the business. At the same time, you can modernize the ones that make business sense because it needs better performance. It needs, you know, something that is, is cheaper or, or maybe just tap into better analytics to get better insights, right? So you're gonna be able to stretch and really have the best of both worlds. That, again, going back to Richard's point, that is meaningful by the business. Not everything has to have that one size fits all set a tool. >>Okay. Thank you. So Richard, you know, talking about data as product, wonder if we could give us your perspectives here, what are the advantages of treating data as a product? What, what role do data products have in the modern data stack? We talk about monetizing data. What are your thoughts on data products? >>So for us, one of the most important data products that we've been creating is taking data that is healthcare data across a wide variety of different settings. So information about patients' demographics about their, their treatment, about their medications and so on, and taking that into a standards format that can be utilized by a wide variety of different researchers because misinterpreting that data or having the data not presented in the way that the user is expecting means that you generate the wrong insight. And in any business, that's clearly not a desirable outcome, but when that insight is so critical, as it might be in healthcare or some security settings, you really have to have gone to the trouble of understanding the data, presenting it in a format that everyone can clearly agree on. And then letting people consume in a very structured, managed way, even if that data comes from a variety of different sources in, in, in the first place. And so our data product journey has really begun by standardizing data across a number of different silos through the data mesh. So we can present out both internally and through the right governance externally to, to researchers. >>So that data product through whatever APIs is, is accessible, it's discoverable, but it's obviously gotta be governed as well. You mentioned you, you appropriately provided to internally. Yeah. But also, you know, external folks as well. So the, so you've, you've architected that capability today >>We have, and because the data is standard, it can generate value much more quickly and we can be sure of the security and, and, and value that that's providing because the data product isn't just about formatting the data into the correct tables, it's understanding what it means to redact the data or to remove certain rows from it or to interpret what a date actually means. Is it the start of the contract or the start of the treatment or the date of birth of a patient? These things can be lost in the data storage without having the proper product management around the data to say in a very clear business context, what does this data mean? And what does it mean to process this data for a particular use case? >>Yeah, it makes sense. It's got the context. If the, if the domains own the data, you, you gotta cut through a lot of the, the, the centralized teams, the technical teams that, that data agnostic, they don't really have that context. All right. Let's send Justin, how does Starburst fit into this modern data stack? Bring us home. >>Yeah. So I think for us, it's really providing our customers with, you know, the flexibility to operate and analyze data that lives in a wide variety of different systems. Ultimately giving them that optionality, you know, and optionality provides the ability to reduce costs, store more in a data lake rather than data warehouse. It provides the ability for the fastest time to insight to access the data directly where it lives. And ultimately with this concept of data products that we've now, you know, incorporated into our offering as well, you can really create and, and curate, you know, data as a product to be shared and consumed. So we're trying to help enable the data mesh, you know, model and make that an appropriate compliment to, you know, the, the, the modern data stack that people have today. >>Excellent. Hey, I wanna thank Justin Theresa and Richard for joining us today. You guys are great. I big believers in the, in the data mesh concept, and I think, you know, we're seeing the future of data architecture. So thank you. Now, remember, all these conversations are gonna be available on the cube.net for on-demand viewing. You can also go to starburst.io. They have some great content on the website and they host some really thought provoking interviews and, and, and they have awesome resources, lots of data mesh conversations over there, and really good stuff in, in the resource section. So check that out. Thanks for watching the data doesn't lie or does it made possible by Starburst data? This is Dave Valante for the cube, and we'll see you next time. >>The explosion of data sources has forced organizations to modernize their systems and architecture and come to terms with one size does not fit all for data management today. Your teams are constantly moving and copying data, which requires time management. And in some cases, double paying for compute resources. Instead, what if you could access all your data anywhere using the BI tools and SQL skills your users already have. And what if this also included enterprise security and fast performance with Starburst enterprise, you can provide your data consumers with a single point of secure access to all of your data, no matter where it lives with features like strict, fine grained, access control, end to end data encryption and data masking Starburst meets the security standards of the largest companies. Starburst enterprise can easily be deployed anywhere and managed with insights where data teams holistically view their clusters operation and query execution. So they can reach meaningful business decisions faster, all this with the support of the largest team of Trino experts in the world, delivering fully tested stable releases and available to support you 24 7 to unlock the value in all of your data. You need a solution that easily fits with what you have today and can adapt to your architecture. Tomorrow. Starbust enterprise gives you the fastest path from big data to better decisions, cuz your team can't afford to wait. Trino was created to empower analytics anywhere and Starburst enterprise was created to give you the enterprise grade performance, connectivity, security management, and support your company needs organizations like Zolando Comcast and FINRA rely on Starburst to move their businesses forward. Contact us to get started.

>>In 2011, early Facebook employee and Cloudera co-founder Jeff Ocker famously said the best minds of my generation are thinking about how to get people to click on ads. And that sucks. Let's face it more than a decade later organizations continue to be frustrated with how difficult it is to get value from data and build a truly agile data driven enterprise. What does that even mean? You ask? Well, it means that everyone in the organization has the data they need when they need it. In a context that's relevant to advance the mission of an organization. Now that could mean cutting costs could mean increasing profits, driving productivity, saving lives, accelerating drug discovery, making better diagnoses, solving, supply chain problems, predicting weather disasters, simplifying processes, and thousands of other examples where data can completely transform people's lives beyond manipulating internet users to behave a certain way. We've heard the prognostications about the possibilities of data before and in fairness we've made progress, but the hard truth is the original promises of master data management, enterprise data, warehouses, data, Mars, data hubs, and yes, even data lakes were broken and left us wanting for more welcome to the data doesn't lie, or does it a series of conversations produced by the cube and made possible by Starburst data. >>I'm your host, Dave Lanta and joining me today are three industry experts. Justin Borgman is this co-founder and CEO of Starburst. Richard Jarvis is the CTO at EMI health and Theresa tongue is cloud first technologist at Accenture. Today we're gonna have a candid discussion that will expose the unfulfilled and yes, broken promises of a data past we'll expose data lies, big lies, little lies, white lies, and hidden truths. And we'll challenge, age old data conventions and bust some data myths. We're debating questions like is the demise of a single source of truth. Inevitable will the data warehouse ever have feature parody with the data lake or vice versa is the so-called modern data stack simply centralization in the cloud, AKA the old guards model in new cloud close. How can organizations rethink their data architectures and regimes to realize the true promises of data can and will and open ecosystem deliver on these promises in our lifetimes, we're spanning much of the Western world today. Richard is in the UK. Teresa is on the west coast and Justin is in Massachusetts with me. I'm in the cube studios about 30 miles outside of Boston folks. Welcome to the program. Thanks for coming on. Thanks for having us. Let's get right into it. You're very welcome. Now here's the first lie. The most effective data architecture is one that is centralized with a team of data specialists serving various lines of business. What do you think Justin? >>Yeah, definitely a lie. My first startup was a company called hit adapt, which was an early SQL engine for IDU that was acquired by Teradata. And when I got to Teradata, of course, Terada is the pioneer of that central enterprise data warehouse model. One of the things that I found fascinating was that not one of their customers had actually lived up to that vision of centralizing all of their data into one place. They all had data silos. They all had data in different systems. They had data on-prem data in the cloud. You know, those companies were acquiring other companies and inheriting their data architecture. So, you know, despite being the industry leader for 40 years, not one of their customers truly had everything in one place. So I think definitely history has proven that to be a lie. >>So Richard, from a practitioner's point of view, you know, what, what are your thoughts? I mean, there, there's a lot of pressure to cut cost, keep things centralized, you know, serve the business as best as possible from that standpoint. What, what is your experience, Joe? >>Yeah, I mean, I think I would echo Justin's experience really that we, as a business have grown up through acquisition, through storing data in different places sometimes to do information governance in different ways to store data in, in a platform that's close to data experts, people who really understand healthcare data from pharmacies or from, from doctors. And so, although if you were starting from a Greenfield site and you were building something brand new, you might be able to centralize all the data and all of the tooling and teams in one place. The reality is that that businesses just don't grow up like that. And, and it's just really impossible to get that academic perfection of, of storing everything in one place. >>Y you know, Theresa, I feel like Sarbanes Oxley kinda saved the data warehouse, you know? Right. But you actually did have to have a single version of the truth for certain financial data, but really for those, some of those other use cases, I, I mentioned, I, I do feel like the industry has kinda let us down. What's your take on this? Where does it make sense to have that sort of centralized approach versus where does it make sense to maybe decentralized? >>I, I think you gotta have centralized governance, right? So from the central team, for things like swans Oxley, for things like security, for certain very core data sets, having a centralized set of roles, responsibilities to really QA, right. To serve as a design authority for your entire data estate, just like you might with security, but how it's implemented has to be distributed. Otherwise you're not gonna be able to scale. Right? So being able to have different parts of the business really make the right data investments for their needs. And then ultimately you're gonna collaborate with your partners. So partners that are not within the company, right. External partners, we're gonna see a lot more data sharing and model creation. And so you're definitely going to be decentralized. >>So, you know, Justin, you guys last, geez, I think it was about a year ago, had a session on, on data mesh. It was a great program. You invited JAK, Dani, of course, she's the creator of the data mesh. And her one of our fundamental premises is that you've got this hyper specialized team that you've gotta go through. And if you want anything, but at the same time, these, these individuals actually become a bottleneck, even though they're some of the most talented people in the organization. So I guess question for you, Richard, how do you deal with that? Do you, do you organize so that there are a few sort of rock stars that, that, you know, build cubes and, and the like, and, and, and, or have you had any success in sort of decentralizing with, you know, your, your constituencies, that data model? >>Yeah. So, so we absolutely have got rockstar, data scientists and data guardians. If you like people who understand what it means to use this data, particularly as the data that we use at emos is very private it's healthcare information. And some of the, the rules and regulations around using the data are very complex and, and strict. So we have to have people who understand the usage of the data, then people who understand how to build models, how to process the data effectively. And you can think of them like consultants to the wider business, because a pharmacist might not understand how to structure a SQL query, but they do understand how they want to process medication information to improve patient lives. And so that becomes a, a consulting type experience from a, a set of rock stars to help a, a more decentralized business who needs to, to understand the data and to generate some valuable output. >>Justin, what do you say to a, to a customer or prospect that says, look, Justin, I'm gonna, I got a centralized team and that's the most cost effective way to serve the business. Otherwise I got, I got duplication. What do you say to that? >>Well, I, I would argue it's probably not the most cost effective and, and the reason being really twofold. I think, first of all, when you are deploying a enterprise data warehouse model, the, the data warehouse itself is very expensive, generally speaking. And so you're putting all of your most valuable data in the hands of one vendor who now has tremendous leverage over you, you know, for many, many years to come, I think that's the story of Oracle or Terra data or other proprietary database systems. But the other aspect I think is that the reality is those central data warehouse teams is as much as they are experts in the technology. They don't necessarily understand the data itself. And this is one of the core tenets of data mash that that jam writes about is this idea of the domain owners actually know the data the best. >>And so by, you know, not only acknowledging that data is generally decentralized and to your earlier point about, so Oxley, maybe saving the data warehouse, I would argue maybe GDPR and data sovereignty will destroy it because data has to be decentralized for, for those laws to be compliant. But I think the reality is, you know, the data mesh model basically says, data's decentralized, and we're gonna turn that into an asset rather than a liability. And we're gonna turn that into an asset by empowering the people that know the data, the best to participate in the process of, you know, curating and creating data products for, for consumption. So I think when you think about it, that way, you're going to get higher quality data and faster time to insight, which is ultimately going to drive more revenue for your business and reduce costs. So I think that that's the way I see the two, the two models comparing and con contrasting. >>So do you think the demise of the data warehouse is inevitable? I mean, I mean, you know, there Theresa you work with a lot of clients, they're not just gonna rip and replace their existing infrastructure. Maybe they're gonna build on top of it, but the, what does that mean? Does that mean the ed w just becomes, you know, less and less valuable over time, or it's maybe just isolated to specific use cases. What's your take on that? >>Listen, I still would love all my data within a data warehouse would love it. Mastered would love it owned by essential team. Right? I think that's still what I would love to have. That's just not the reality, right? The investment to actually migrate and keep that up to date. I would say it's a losing battle. Like we've been trying to do it for a long time. Nobody has the budgets and then data changes, right? There's gonna be a new technology. That's gonna emerge that we're gonna wanna tap into. There's gonna be not enough investment to bring all the legacy, but still very useful systems into that centralized view. So you keep the data warehouse. I think it's a very, very valuable, very high performance tool for what it's there for, but you could have this, you know, new mesh layer that still takes advantage of the things. I mentioned, the data products in the systems that are meaningful today and the data products that actually might span a number of systems. Maybe either those that either source systems, the domains that know it best, or the consumer based systems and products that need to be packaged in a way that be really meaningful for that end user, right? Each of those are useful for a different part of the business and making sure that the mesh actually allows you to lose all of them. >>So, Richard, let me ask you, you take, take Gemma's principles back to those. You got, you know, the domain ownership and, and, and data as product. Okay, great. Sounds good. But it creates what I would argue or two, you know, challenges self-serve infrastructure let's park that for a second. And then in your industry, one of the high, most regulated, most sensitive computational governance, how do you automate and ensure federated governance in that mesh model that Theresa was just talking about? >>Well, it absolutely depends on some of the tooling and processes that you put in place around those tools to be, to centralize the security and the governance of the data. And, and I think, although a data warehouse makes that very simple, cause it's a single tool, it's not impossible with some of the data mesh technologies that are available. And so what we've done at EMI is we have a single security layer that sits on top of our data mesh, which means that no matter which user is accessing, which data source, we go through a well audited well understood security layer. That means that we know exactly who's got access to which data field, which data tables. And then everything that they do is, is audited in a very kind of standard way, regardless of the underlying data storage technology. So for me, although storing the data in one place might not be possible understanding where your source of truth is and securing that in a common way is still a valuable approach and you can do it without having to bring all that data into a single bucket so that it's all in one place. >>And, and so having done that and investing quite heavily in making that possible has paid dividends in terms of giving wider access to the platform and ensuring that only data that's available under GDPR and other regulations is being used by, by the data users. >>Yeah. So Justin mean Democrat, we always talk about data democratization and you know, up until recently, they really haven't been line of sight as to how to get there. But do you have anything to add to this because you're essentially taking, you know, doing analytic queries and with data, that's all dispersed all over the, how are you seeing your customers handle this, this challenge? >>Yeah, I mean, I think data products is a really interesting aspect of the answer to that. It allows you to, again, leverage the data domain owners, people know the data, the best to, to create, you know, data as a product ultimately to be consumed. And we try to represent that in our product as effectively, almost eCommerce, like experience where you go and discover and look for the data products that have been created in your organization. And then you can start to consume them as, as you'd like. And so really trying to build on that notion of, you know, data democratization and self-service, and making it very easy to discover and, and start to use with whatever BI tool you, you may like, or even just running, you know, SQL queries yourself. >>Okay. G guys grab a sip of water. After the short break, we'll be back to debate whether proprietary or open platforms are the best path to the future of data excellence. Keep it right there.

>>Okay. We're back in Boston covering AWS reinvent 2022. This is our second live reinvent. We've done the other ones, uh, in between as digital. Uh, my name is Dave Lanta and you're watching the cube. Peter McKay is here. He's the CEO of sneaking ad Shani is the chief technical officer guys. Great to see you again. Awesome. Being here in Boston >>In July. It is Peter. You can't be weather's good weather. Yeah, red SOS. Aren't good. But everything else >>Is SOS are ruin in our sub, you know, >>Hey, they're still in the playoff, the hunt, you >>Know, all you gotta do is make it in. Yes. >>Right. And there's a new season. Simple >>Kinda like hockey, but you know, I'm worried they're gonna be selling at the trading >>Deadline. Yeah. I think they should be. I think it's you think so it's not looking good. Oh, >>You usually have a good angle on this stuff, but uh, well, Hey, we'll see. We'll go. I got a lot of tickets. We'll go and see the Yankees at least we'll see a winning team. Anyway, we last talked, uh, after your fundraising. Yeah. You know, big, big round at your event last night, a lot of buzz, one of the largest, I think the largest event I saw around here, a lot of good customers there. >>It's great. Great time. >>So what's new. Give us the update. You guys have made some, an acquisition since then. Integration. We're gonna talk >>About that. Yeah. It's been, uh, a lot has happened. So, uh, the business itself has done extremely well. We've been growing at 170% year, over year, a hundred percent growth in our number of customers added. We've done six acquisitions. So now we have, uh, five products that we've added to the mix. We've tripled the size of the company. Now we're 1300 people, uh, in the organization. So quite a bit in a very short period of time. >>Well, and of course my, in my intro, I, I said, reinvent, I'm getting ahead of myself. Right. >>Of course we'll >>Reinforced. We'll be at reinve >>In November. Are that's the next one at >>Reinforced. We've done a lot of reinvents by the way, you know? >>So there's a lot, lot of reinvention >>Here. So of course, well, you're reinventing security, right? Yes. So, you know, I try to, I think about when I go to these events, like, what's the takeaway, what's the epiphany. And we're really seeing the, the developer security momentum, and it's a challenge. They gotta worry about containers. They gotta worry about run time. They gotta worry about platform. Yeah. You guys are attacking that problem. Maybe describe that a >>Little bit for us. Yeah. I mean, for years it was always, um, you know, after the fact production fixing security in run time and billions and billions of dollars spent in fixing after the fact. Right. And so the realization early on with the was, you know, you gotta fix these issues earlier and earlier, we started with open source was the first product at wait. Then six, six years ago, then we added container security and we added infrastructure's code. We added code security. We added, um, most recently cloud security with the F acquisition. So one platform, one view that a developer can look at to fix all the issues through the, be from the beginning, all the way through the software development life cycle. So we call it developer security. So allowing developers to develop fast, but stay secure at the same time. >>So I like the fact that you're using some of your capital to do acquisitions. Yeah. Now a lot of M and a is, okay, we're gonna buy this company. We're gonna leave them alone. You guys chose to integrate them. Maybe describe what that process was like. Yeah. Why you chose that. Yeah. How hard it was, how long it took. Take us through that. >>Yeah. Yeah. I'll give, uh, two examples, maybe one on sneak, which was an acquisition of, of the company that was focused on, uh, code analysis, actually not for security. And we have identified the merit of what we need in terms of the first security solution, not an ability to take a security product and put it in the end of developer, but rather build something that will build into the dev motion, which means very fast, very accurate things that it can rely on source and not just on the build code and so on. And we have built that into the platform and by that our customers can gain all of their code related issues together with all of their ISE related issues together with all of the container issues in one platform that they can prioritize accordingly. >>Yeah. Okay. So, so talk more about the, the, the call, the few, the sneak cloud, right? Yeah. So the few name goes away. I presume, right. Or yes, it does. Okay. So you retire that and bring it in the brand is sneak. Yeah. Right. So talk about the cloud, what it does, what problems >>It's solving. Yeah. Awesome. And, and this goes exactly the same. As we mentioned on, on the code, we have looked at the, the, the cloud security solutions for a while now. And what we loved about the few team is that they were building their product with their first approach. Okay. So the notion is as followed as you are, you know, you're a CSO, you have your pro you have your program, you're looking, you have different types of controls and capabilities. And your team is constantly looking for threats. When we are monitoring your cloud environment, we can detect problems like, you know, your FL bucket is not exposing the right permissions and is exposed to the world or things like that. But from a security perspective, it might be okay to stop there. But if you're looking at an operation perspective, you need to know who needs to fix, how do they need to fix it? >>Where do they need to fix it? What will the be the impact if they would fix it? So what do we actually doing is we are connecting all the dots of the platform. So on one end, you know, the actual resources that are running and what's the implication in the actual deployed environment. On the other end, we get correlation back to the actual code that generates that. And then I can give that context both to the security person, the context of how it affects the application. But more importantly, the context for the developer is required to fix the problem. What's the context of the cloud. Yeah. And a lot of things are being exposed this way. And we can talk about that. Uh, >>So this is really interesting because, and look, I love AWS to do an amazing job. One of the other things I really like about 'em is it seems like they're not trying to go hard and monetize their security products. Mm-hmm, they're leaving that to the ecosystem, which I like. Yeah. Microsoft taken a little different approach, right? Yeah, yeah, yeah. Ton a lot. But this, this, this example you're giving ad about the S3 bucket. So we heard in the keynotes yesterday about, you know, reasoning, AI reasoning, they said, we can say, is this S3 bucket exposed to the public? We can do that with math. Right. Yeah. But you're what I'm inferring is you don't stop there. Yeah. Yeah. There's a lot of other stuff that has to, >>And sometimes have to, not as simple, just as a configuration change, sometimes the correlation between what your application is doing affects what is the resulted experience of, you know, the remote user or in this case, the attacker, right. I mean, >>The application has access, who has access to the application, is this, this the chain. >>So propagates, you have to, you have to have a, a solution that looks both at have very good understanding of the application context. A very good understanding of what we refer to as the application graph, like understanding how it works, being able to analyze that and apply the same policies, both at development time, as well as run time. >>So there's, there's human to app. There's also a machine to machine. Can you guys help with that problem as well? Or is that sort of a futures thing or >>Could you, I'm not sure. I understand what >>Referring, so machines talking to machines, right. I mean, there's data flowing. Yep. You know, between those machines, right. It's not just the humans interacting with the application. Is that a trend that you see and is that something that you guys can solve? >>So at, at the end of the day, there is a lot of automation that happens both for, by humans for good reasons, as well as by humans for bads. Right. <laugh> and, and the notion is that we are really trying to focus on what matters to the developer as they're trying to improve their business around that. So both improves making sure they know, you know, quality problems or things of this kind. But as part of that, more importantly, when we're looking at security as a quality problem, making sure that we have a flow in the development life cycle that streamline what the developer is expecting to do as they're building the solution. And if every single point, whether it's the ID, whether it's the change management, whether it's the actual build, whether it's the deployed instance on the cloud, making sure that we identify with that and connect that back to the code. >>Okay. So if there's machine automation coming in, that shouldn't be there, you can sort of identify that and then notify remediate or whatever action should be >>Taken. Yeah. Identify, identify remediate. Yep. >>Yeah. We, we really focus on making sure that we help developers build better products. So our core focus is identify areas where the product is not built way in a good way, and then suggest the corrective action that is required to make that happen. >>And I think part of this is the, you know, just, uh, the speed of the software development today. I mean, you look at developers are constantly and not just look at sneak you're, you're trying to get so much more productivity outta the developers that you have. Every company is trying to get more productivity out of developers, incredible innovation, incredible pace, get those is a competitive advantage. And so what we're trying to do is we make it easier for developers to go fast innovate, but also do it securely and embed it without slowing them down, develop fast and secure. >>So again, I love, I love AWS love what they're doing. We heard, uh, yesterday from, from CJ, you know, a lot of talk about, you know, threat detection and, you know, some talk about DevOps, et cetera. But yeah, I, I, I didn't hear a lot about how to reduce the complexity for the CSO. And the reason I bring this up is it feels like the cloud is now the first level of defense and the CISO is, is becoming the next level, which is on the developer. So the developer is becoming responsible for security at a whole shift left, maybe shield. Right. But, but shift left is becoming critical. Seems like your role and maybe others in the ecosystem is to address my concern about simplifying the life of the CISO. Is that a reasonable way to think about it? I >>Think it's changing the role of the CISO. How so? You know, really it's, I, I think it's before it, in this, in the security organization and D you should chime in here is, you know, it used to be, I did, I owned all application security, I owned the whole thing and they couldn't keep up. Like, I think it's just every security organization is totally overwhelmed. And so they have to share the responsibility. They have to get that fix the issues earlier and earlier, because it's waiting too long. It's after the fact. And then you gotta throw this over the fence and developers have to fix it. So they've gotta find a new way because they're the bottleneck they're slowing down the company from, in innovating and bringing these applications to market. So we are the kind of this bridge between the security teams that wanna make sure the, that we're staying secure and the development organizations and engineering and CEOs go fast. We need you guys to go faster and faster. So we, we tend to be the bridge between the two of them. >>One of the things I really love happening these days is that we change the culture of the organization from a culture where the CSO is trying to, you know, push and enforce and dictate the policy, which, which they should, but they really wanna see the development team speak up like that. The whole motion of DevOps is that we are empowering them to make the decisions that are right for the business, right? And then there is a gap because on one hand, this is always like, you need to do this, you need to do this. You need to do that. And the dev teams don't understand how that impacts their business. Good enough. And they don't have the tools and, you know, the ability to add a source problem. So with the solution liken, we really empower the developers to bake security as part of their cycle, which is what was done in many other fields, quality, other things, everything, it, everything moves into development already, right? So we're doing that. And the entire discussion now changes into an enablement discussion. >>So interesting. Cause you saw, this is the role of the CSOs changing. How so? I see that in a way like frees, sneak the CSO with the cloud is becoming a compliance officer. Like you do this, you do this, you do this, you do this, you third >>One would take a responsibility >>Trying. Yeah. Right, right. And so you're flipping that equation saying, Hey, we're gonna actually make this an accelerant to your business. >>So, so set the policy, determine compliance, but make sure that the teams, the developers are building applications in compliance with your policy. Right. So make sure and, and don't allow them to do something. If they're doing, if they're developing an application with a number of vulnerabilities, you can stop that from happening so you can oversee it, but you don't have to be the one who owns it all the way through from beginning to, >>Or, or get it before it's deployed. So you don't have to go back after the fact and, and remediate it with, you know, but, >>But think about deploy, they're deploying apps today. I mean, they're updating by the hour, right? Where, you know, six years ago, five years ago, two years ago was every six to nine months. Right? So the pace of this innovation from developers is so fast that the old way of doing security can't keep up. Like they're built for six month release cycles. This is six hour release cycles. And so we had to, it has to change security. Can't stay the way it is. So what we've been doing for se seven years for application security is exactly what we're doing for cloud security is moving all that earlier. All these products that we've been building over the years is really taking these afterthought security components and bringing 'em all earlier, you know, bringing everything like cloud security is done after the fact. Now we can take those issues and bring 'em right to the developers who created that and can fix the issues. So it's code to cloud back to code in a very automated fashion. So doesn't slow developers down. >>Okay. So what's the experience. We all know there's, everybody has more than one cloud. What's the experience across clouds. Can you create a consistent, continuous experience, cloud agnostic, >>Agnostic, cloud agnostic, uh, development environment, agnostic, you know, language agnostic. So that's kind of the beauty oft where you have maybe other certain tools for certain clouds, uh, or certain languages or certain development environments, but you have to learn different tools, you know, and, and they all roll up to security in a different way. And so what we have done is consolidated all that spend for open source security, container security infrastructure, now, cloud security, all that spend and all that fragmentation all under one platform. So it's one company that brings all those pieces >>Together. So it's a single continuous experience. Yeah. The developer experience you're saying is identical. Yes. >>Actually one product >>It's entitlement that we're getting. Yes. So you're hiding the underlying complexities of the respective clouds and those primitives developer doesn't have to worry about them. No, I call that a super cloud super >>Cloud. >>Okay. But no, but essentially that's what you're, you're building, building on the, on this ed Walsh would say on the shoulders of giants. Yeah, exactly. You know, you don't have to worry about the hyperscale infrastructure. Yep. Right. That you're building a layer of value on top of that. Yes. Is, is that essentially a PAs layer or is it, is it, can I think of it that way or is it not? Hmm. Is it platform? I >>Mean, yeah. I, I, I would say that at the end of the day, the, the way developers want to use a security tool is the same. Right. So we expose our functionality to them in those ways, if you're using, you know, uh, uh, one GI repository or another, if you're using one cloud or we, we are agnostic to data, don't, it's not, it doesn't really affect us in that manner. Um, I want to add another thing about the, the experience and associated with the consolidation that Peter referred to, uh, earlier, when you have a motion that automatically assess, you know, uh, problems that the developer is putting as part of the change management, as example, you do creating pool request. Now adding more capabilities into that motion is easy. So from enablement of the team, you can add another functionality, add cloud at ISC, add code and so on like that, because you already, you already made the decisions on how you are looking at that. And now you're integrated at, into your developer workflows, >>Right? So it's, it's already, it's already integrated for open source, adding container and ISD is real easy. It's all, you've already done all the integrations. And so for us going to five products and eventually 6, 7, 8, all, all based on the integrations that you already have in the same workflows that developers have become a use accustomed >>To. And that's what we, a lot of work from the company perspective. Right. >>I can ask you about another sort of trend we're seeing where you see Goldman Sachs last reinvent announced a cloud product, essentially bringing their data, their tools, their software. They're gonna run it on AWS at the snowflake summit, uh, capital one announced the service running on snowflake, Oracle by Cerner, right? Yeah. You know, they're gonna be, do something on OCI. Of course, make 'em do that. But it's, it's a spin on Andreessens every company's a software company. It's like every company's now becoming digital, a software company building their own SAS, essentially building their own clouds, or maybe, maybe something they'll be super clouds. Are you seeing industry come to sneak and say, Hey, help us build products that we can monetize >>There companies. So, first off, I think kind of the first iteration is, you know, all these industries of becoming software driven, like you said, and more software is more software risk. And so that kind of led us down this journey of now financial services, you know, tech, you know, media and entertainment, financial services, healthcare. Now it's this long tail of, of low tech. Yeah. Within those companies, they are offering services to the other parts of the organization. We have >>So far, mostly >>Internal, mostly internal, other than the global SI. And some of the companies who do that for a living, you know, they build the apps for companies and they are offering a sneak service. So before I give you these, I update these applications. I'm gonna make sure I'm running. I'm, I'm, I'm signifying those applications to make sure that they're secure before you get them. And so that now a company like a capital one coming to us saying, I wanna offer this to others. I think that's a, that's a leap because you know, companies are taking on security of someone else's and I think that's a, that's not there yet. It may be, >>Do you think it'll happen? >>We do have the, uh, uh, threat Intel that we, we have a very, a very strong security group that constantly monitors and analyzing the threat. And we create this vulnerability database. So in open sources, an example, we're the fact of standard, uh, in the field. So many of our partners are utilizing the threat Intel feed of snake as part of their offering. Okay. If you go to dock as an example, you can scan with, with snake intelligence immediately out of the gate over there, right? Yeah. >>And tenable, rapid seven trend micro. They all use the vulnerability database as well. Okay. So a lot of financial institutions use it because they had, they'd have seven, 10 people doing re security research on their own. And now they can say, well, I don't have to have those seven. I've got the industry standard for vulnerability database from Steve. >>And they don't have to throw out their existing tool sets where they have skills. >>Yes, exactly. >>Peter bring us homes, give us the bumper sticker, summarize, you know, reinforce and kind what we can expect going forward. >>Yeah, no, I mean, we're gonna continue the pace. We don't see anything slowing, slowing us down in terms of, um, just the number of customers that are, that are shifting left. Everybody's talking about, Hey, I need to embed this earlier and earlier. And I think what they're finding is this, this need to rein reinnovate like get innovation back into their business. And a lot of it had to slow down because, well, you know, you, we can't let developers develop an app without it going through security. And that takes time. It slows you down and allows you not to like slow the pace of innovation. And so for us, it's it help developers go fast, incredibly, you know, quickly, aggressively, creatively, but do it in a secure way. And I think that balance, you know, making sure that they're doing what they're doing, they're increasing developer productivity, increasing the amount of innovation that developers are trying to do, but you gotta do it securely. And that's where we compliment really what every CEO is pushing companies. I need more productivity. I need more aggressive creativity, innovation, but you better be secure at the same time. And that's what we bring together for our customers. >>And you better do that without slowing us down. That's >>Don't trade off, slow >>Us down. Always had to make. Yes, guys. Thanks so much for coming to the cube. Thanks, David. Always great to see you guys see ID. Appreciate it. All right. Keep it right there. This is the Cube's coverage of reinforced 2022 from Boston. We'll be right back right after the short break.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Welcome back to HPE. Discover 2022. My name is Dave Lanta. I'm here with my co-host John fur. John we've been watching the evolution of H HP to HPE. We've seen GreenLake when Antonio Neri, I called it. I called it burn the boats. He goes, no, no, no, it wasn't burn the boats. I said, well, okay, burn the bridges. But it was all in on as a service on, on GreenLake. And we're gonna talk about that. Brad Shapiro is here. He's the vice president and managing director of the enterprise business at HPE financial services. Brad. Good to see him. Good to see >>You as well. >>Yeah, you guys got it all started. When, when Antonio kinda laid down, the gauntlet said, this is where we're going. Let's make it happen now. Cause the first place he turned I would imagine is the financial services said, okay, how do we start this today? Can you help us? And they take us back to that >>And yeah, sure. So, you know, uh, yeah, HP financial services, um, it's kind of a foundational element cuz when you think about it, asset management is really what we're doing here. And I know asset management's a, a big word, right? And it can mean lots of things to, to different people. Um, in this context, uh, we started looking at how do customers manage assets over the life cycle and a lot of customers while they were interested in a consumption model and looking at GreenLake for their private cloud, they were certainly looking at public cloud for certain workloads and then maybe even traditional data center for other activities that, that they're running. So it's really that hybrid environment. Uh, but they were stuck going well, Hey, I'm in a CapEx model today. How do I get out of CapEx and really get into this hybrid model? >>And that's where asset management comes in. So one of the, the biggest initial focus is, and we continue to have that focus. We call it our accelerated migration offer and it's really us going in and acquiring the customer assets, moving it on the HPE balance sheet and then figuring out what are we gonna do with those assets, which are gonna stay in use under a consumption model, which are excess. And we can put through our, uh, asset up cycling process, we monetize the majority of that, put that back into reuse and then maybe a small amount gets recycled. So, so really focused on the assets and accelerating customers transition to GreenLake. Did you >>See, or are you seeing a difference between like Le traditional leasing customers who already have kind of on that model versus like what you just described as sort of the, the CapEx was more complicated, you gotta get, I presume procurement involved the legal issues and was there a lot less, was it less friction with the, the leasing customers? Well, >>You know, I, I look at leasing and financing, very similar to CapEx. It's, it's a much more traditional model versus this new as a service experience. Um, so if, if they were in a leasing model, we could convert those leases into GreenLake. I wouldn't say one was any more difficult than the other. Yeah. Um, they were both really traditional mindset, um, and not really looking at a consumption model. So I think we had our fair share of both. And I think we, we have and are able to address both customers moving in into a consumption >>Mode. Right. How does this tie into sustainability? Because you know, we have on one end of the spectrum, the, the high end sustainability, you know, the, the science and sure. And the behind it, tactically speaking companies still now want to operate in this kind of, there's a sustainable angle here. Yeah. Talk about that piece of it. How does that tie in obviously consumption versus CapEx you're building, you're not building, what, what does that thread through the sustainability angle? >>Yeah. So, so first let me just say sustainability is really important to our customers. Um, and, and we're seeing it all over and it is real. Um, the good thing is that you can get business value out of the solutions and have a more sustainable model. So when I think about, and I talk to customers about sustainability, uh, there's a number of fronts they're focused on one, their customers believe it's important, right? So, so they're focused on making sure they're driving sustainable models. Uh, I've seen an increasing number of customers, both commercial and public sector have sustainability requirements in their tenders, in their RFPs. And you have to be able to, to comply with those. Um, second, uh, they, they look at it and go, how do I attract talent? It's increasingly important for them to attract talent. And then really if you, because >>They wanna work for a mission driven company that's >>Sustainable. Absolutely. Absolutely. And, and the third area is investors. You know, the investment community is now looking at ESG and whole and you know, certainly environmental impacts, um, in where they're making an investment. So quick personal story, I was talking, uh, to a friend of mine who works for a hedge fund and he was telling me over the last year, they've hired a whole team. That's focused on just doing analysis of companies, ESG initiatives, determining where they're gonna invest their money. So it's, it's a wall street thing now. So this is real from a number of angles where, where sustainability has an impact. Now, how we play in that. Um, clearly when you go to a GreenLake consumption model, the idea is improving utilization of the asset. So driving higher utilization means you need less assets. You know, over time, the, the secret is we're gonna sell you less, right? >>You're gonna have less assets, but you're gonna have higher utilization. That's good for the environment where HPE Fs comes in is when those assets are done. We put those assets back into reuse. So we have a remark, we have remarketing facilities, one in, in Andover, mass, one in kin Scotland. And then we have 80 different facilities. We have partnerships around the world and our focus is how do we drive more reuse, 85% of the assets we get back, go into reuse. And when you look at servers and PCs and things like that, it's over 95% go into reuse. So a real focus on reuse is good for the environment as well. And then needless to say, the new technology that goes into a GreenLake deal, we're seeing like 30% energy savings coming, coming out of those environments. So all really good stuff related to it's >>Interesting. I mean, a couple points there is one is, you know, Benoff kind of got it all started pre pandemic. He was out talking about, you know, sustainability and ESG. And a lot of people were like, no way. It's all about bottom line profits. And so he was ahead of that. And I guess, you know, back to at least you were, oh, you were always in the residual value game, but now it's a little different, isn't it? Absolutely. It's, it's it's yes. You gotta figure out what the value of that asset's gonna be, but also there's a sustainability aspect of it as >>Well. Yeah, absolutely. And the, the pretty cool thing here is while you drive sustainability, we're also seeing customers that, that go into GreenLake. Um, we had a good example with Kern county, a 42% savings over their CapEx environment when they moved to GreenLake. So it was better for the environment and significant savings. So you can have kind of like have your cake and eat it too. You, you get better environmental, uh, impacts and you're getting better bottom line, uh, performance. >>It's a business case there too do. Now we kind of, I was talking upfront about the, the early days of GreenLake where, you know, they were, it was a financial model. Yeah. And now it's evolving to actually a technology model. We heard Alma with the platform. How has that, or has that changed the way that financial services your >>Group >>Yeah. Approaches the, the, the market. >>Yeah. So, um, yeah, that's a great point. You know, when people talk about GreenLake, they think about the old days. And, and look, I've been around a while. I remember the flex capacity, right? Yeah, of course this isn't flex capacity. I mean, the platform's amazing and it really starts to bring to life the whole thought, when we talk about hybrid, right, there are workloads sure. They might belong best in the public cloud. Right. There, there are workloads that belong best in the private cloud, under the HPE GreenLake model. And there are still workloads that customers may say, Hey, look, I've got legacy applications. I'm gonna continue to run them in a traditional data center. And so from an H P E Fs perspective, you know, we look at this, not as a leasing and financing company, we're looking at this on how do we leverage the customer's existing assets? >>How do we create incremental budget using those existing assets? And then what kind of model best serves that workload? And then how do you optimize the capacity and the spend on that? So, you know, an interesting note in the past year, we put 500 million back into customer budgets by just leveraging their existing it estate. And, and it does, it's not all HPE product, you know, we're, we're, we're monetizing third party products in the data center, in the network, in the workplace. So we can really look at, we call it any tech any time, anywhere we look at all the technology and really assess what's the best way to leverage that investment. Yeah. And, and get the most out of >>It. Yeah. I mean, it's really evolved from just recycling assets for profit, but integrating the business model into the value proposition, the core value proposition in GreenLake. That's great innovation. Um, and, and congratulations on that. Sure. My, my question for you is more kind of zooming out at the market. Mm-hmm <affirmative>, from your perspective in financial services at HPE, what has the pandemic proven to you guys? How has it changed? How you guys work and how has it changed the customer environment? Cuz you mentioned assets. I think real estate. Oh no. One's going back to work. Yeah, no one's been in the office. How has the market changed with hybrids as a steady state now coming outta the pandemic? What are customers doing with the assets? What are some of the trends that you're seeing in the customer base? >>Yeah. So, so look, I'll give you my personal perspective of what I think about as a business leader. And when I talk to customers, I think we're all thinking about the same thing. So I start with experience, what experience do I wanna create for my customers and very closely linked to that, my colleagues, right? So it, the, the people working in our organization, what experience am I creating for them? So they can in turn, create that experience for partners and customers externally. So experience is one thing. The second is innovation, right? We spend a lot of time thinking about what's next? Where do we want to go? What's the innovation and more and more that innovation is all digital, right? So digital transformation is huge within my organization. And it's huge within all of our customers. Dave, I think the last time we talked, I was in my living room on a little laptop screen and zoom and, and I think I use the analogy E every business is now a digital business, even my pizza shop in jerseys. >>Yeah. Right. I mean, everything was online curbside pickup. So what I'm finding is the, the trends in terms of how to leverage technology is how do you create that customer experience? And then how does digital now blend as we're coming out of the pandemic? And, and you're, you know, now able to go into restaurants and stores, how do you blend digital with that in person experience and maybe leverage the best of both. Right. And, and how do you do that in a seamless way to really give customers choice and give them that smooth, seamless experience. So that, that's what I see happening. And you know, what we are trying to do with our asset management plays with the financial modeling we do is how do we get more of that spend going to innovation versus maintenance. And, and that's a big key because, you know, you have to be fast. So I talk about innovation. I talk about customer experience, speed to market. I mean, you know, and the bar keeps getting higher, right? It's like, as soon as you think you're fast, you're slow. We, because you have to keep, it all keeps rolling. >>We heard yesterday on the cube from, uh, one of the HP point, next executives said, you gotta perform and transform >>At the >>Same time at the same time. And you gotta know where the people are gonna land. Absolutely. And how the assets are gonna be distributed. >>And to your point, Brad, you know, from our virtual interview, you're so right. I mean, every business has to be a digital business. And you know, my, my personal story, John, you know, my brother Richie was the executive chef at legal seafood. Right. Pandemic. So then that was a, a place you wanted to go to that restaurant, famous restaurant in Boston when they reopened, they weren't ready. Right. They didn't have the digital story together. They ended up having to, we were just at Smith and Linsky, they ended up selling to Smith and Wilensky's oh, and you, you drive around, you see a lot of these retail businesses is shut down. Yeah. Right. And so, okay. So we're, they weren't able to get through that, you know, cross that chasm in digital transformation. Yeah. A lot of businesses were able to and make it a tailwind. >>Yeah. And, and look, the other thing I think all businesses are focused on right now, uh, with the labor market is talent. And, and so when you think about all of these things tying together, you want to drive, uh, you know, innovation. You want to drive your digital transformation. You wanna make that environmentally sustainable. And, and I think all of that, if you start putting all that together, those are the companies that are gonna attract the talent in the marketplace. And, and really there there's a battle for talent and >>You wanna make it profitable. Uh, Brad bureau. Thanks so much for you. Great to see you face to face. >>Yeah. Likewise. Thanks. Thanks. >>All right. Keep it right there, John. And I will be back. We're wrapping up day three of HPE, discover 2022. You're watching the cube.

>>The >>Cube presents HPE discover 2022 brought to you by >>HPE. Hi everybody. Welcome back to day three, the Cube's continuous coverage wall to wall coverage of HPE. Discover 2022. My name is Dave Lanta. I'm here with John furrier. Dave McGraw is here. He's the vice president in the office of the CTO at VMware. And he's joined by Scott. We, the vice president and CTO of global sales for Hewlett Packard enterprise. And we're gonna talk tech, we're gonna talk integration. Co-creation gens. Welcome to the cube. >>Thank you so much, >>Scott, let me, let me ask you a question on the Scott side on the HP, we had the sales executives on the leaders on the sales side. You're on the CTO side with customers. You're in the front lines with customers green. Lake's got traction. I got this 1600 plus customers, 70 services we heard. And just the beginning, when you're out front of customers, you've got the old HPE now the new HPE kind of developing, what are they talking to you guys about? Cause now you have this cloud layer. I call it cloud operations, architecture shift. Yeah. What is the main conversation that you're involved in? >>I think it's driven by fundamentally that customers want to consume differently, right there workloads are ever evolving. You guys have evolved to meet those and since their consumption methods have changed on how they want and right. A lot of it's agility and, and speed of business right. Has, has dramatically shifted. So I think you'll see HPE GreenLake, you know, obviously as the cloud that comes to you, try to meet the problem where the cloud experience is needed. And I think that's the fundamental shift we've seen. I spent a lot of time with customers here at this conference. And as we've moved from cloud first to cloud smart to cloud everywhere, we're sitting in the intersection of cloud ever and delivering the experience together. And I think that's the heart of most of the conversations that are going on. >>Well, VMware, you guys are on, on a cloud. You guys shifted up with the cloud play. That's accelerated the VMware proposition. Now we have yesterday, we were talking to the city, the storage folks, they're provisioning single pane of glass or storage to customers. And whether they wanna pipe it to S3 or develop at the edge, doesn't matter. It's one console. Yeah. That's brand new. That's shipping. >>Yeah. And you know, a lot of it's driven too. I think the days of trap silos of resources that support one line of business are over. So we're talking about cloud agility everywhere, right. And to be able to embrace the cloud in all the locations. Right. And you kind of see folks move beyond just like there's the cloud, it's everywhere. It's the cloud. And so things like storage and fundamental compute and fundamental network operations that we're working on together, I think are where the customers expect us to be. We no longer can just show up. We have to show up and solve and solve before their needs. And I think that's a unique shift in the experience that's going >>On. So when you go back to, you know, Antonio four years ago now said, okay, we're all in. Yeah. On as a service. And so when you do that, you say, okay, we're gonna, we have services. They're gonna help do that. We have financial models that we can take to market immediately. So let's start there. And I would imagine take, so take us back. That's the point at which, you know, you're, you got email, phone ring, whatever let's integrate from an engineering standpoint go yeah. You know, as fast as you can. So what did that mean in terms of an engineer from an engineering perspective between HPE and, and VMware take us through that progression. >>Yeah. No, thanks for the question in your spot on it started with flexible financing models around metered usage. That was sort of the need at the time to now the expectation of engineered integrated solutions where customers don't wanna be in the system integration business anymore. And that requires engineering right. Requires deep innovation partnership to evolve to where the customer's headed, like before they've thought about it. And you'll see, you know, what we've done with vCloud foundation together and the integration within the HP GreenLake ecosystem, what we're doing with unified hybrid cloud views of what's going on, I think requires deep innovation things we're doing with other projects that we're gonna talk about today. Like Monterey capital thunder, our deep integrative innovation projects, where we've got together to try to solve a big problem cross industry that our customers are expecting us to do. And I think that speaks to the spirit of our long partnership together too. It's a business partnership. Of course it's a customer partnership to solve, but it's an innovation partnership. >>I gotta, I gotta ask about the, um, hybrid, obviously hybrids, the steady state. We're all seeing that now multi-cloud is being kicked around, but it's not, multi-cloud in the sense of workload portability so much. It's more of hybrid stitched together. Um, but it's coming fast with a data plane and yeah. The fabric and control planes. Uh, VMware, you guys are talking heavy about cross cloud or multicloud. Absolutely. So this is now brings up the old school interoperability question, right? So GreenLake sits here on premise. You guys have the edge, you get public cloud together. Where's the cross cloud come in. Where are customers doing when they think about cross cloud or, or multicloud? What is that conversation? Is it, Hey, I got Azure cause I got office and teams and I got Amazon over here and I got my on premise edge. Are they moving towards just being agnostic on cloud or is what's the environment? What, what are you crossing in the cloud? What does that mean across the cloud? Can >>You, I mean, from, from our perspective at VMware on premises, it's VMware cloud foundation, having that available, it's a VMware cloud instance, full STD STDC stack, uh, that is interoperable with our VMware cloud instances at the hyperscalers. And so for us, it's really about putting the management and control planes around that so that customers can easily determine where they wanna place workloads and when they need to burst, they need to scale up scale down. They have the flexibility and we wanna make sure all of these capabilities are available with HPE >>Going forward. What's interesting is that, you know, with, with GreenLake, what I like about what I'm seeing is is that, um, the leveling up of the cloud operation model, it's always been DevOps. We've always saw dev stack ops, clearly being operationally with cloud now on premise and edge with public cloud, it's full end to end operational cloud. If you wanna call it that, what is a key technical issue the customers need to do to get that in place? Is it to be DevOps, is that have cloud native applications, um, what kind of managed services, what's the makeup of that operating model for cloud look like? >>Yeah. I think if you talk to any enterprise commercial account, a top account, they'll they'll, if you, they think about how they run their functions, right. And you got, and you spoke to one of them, you have it ops at the bottom, it's a layer cake, right? You have it ops, everybody's deeply looking for AI ops that can remediate and orchestrate and you guys are on that journey as we are, as you move up to devs and dev SecOps, cuz security's critical, you got financial ops cuz we know economic value matters all the way clear up to cloud ops and Mo ops. What we're talking about is building hybrid operating model cause hybrid, it is simplified it where you're out of the stack, we're doing that together as partners and hybrid cloud is multiple consumption methods, but an operating model is encompass encompassing, cyber resiliency, compliance, economic, operational control. >>That's what we're built and edges in there as well. Right? Folks is, and it's not OT and it touching that's happening too, as we build edge tax, but folks need a simplified way. And as you saw in a lot of announcements here, our job was to bridge the cloud locations, right? So the customer didn't have to back to the portability statement you made, we announced a lot here that will allow you to float back and forth. So you have choice, choice and control control is the me is what every customer wants and they want the right workload at the right place at the right time at the right economic with the right capability. So I think that's in our mission together. Right? So, and >>A big part of engineering obviously is, is futures and roadmap. Yeah. Thought you mentioned Monterey cap thunder, you know, Monterey's kind of the smart Nick. One of the mega trends in the industry is Silicon diversity that handle all these new workloads to help with the edge. You know, capital is like the VSAN of memory as I, I would describe it. It obviously fits in there as well. So talk a little bit about the engineering roadmap, whatever you can share with us and how you guys are working together on that. Yeah. >>Yeah. I mean, those are three key projects for us. So there's constant interaction and integration with the HPE engineering team and the VMware team to make sure we bring those solutions to market with full capability. And for us, ultimately it's taking that technology and having it available in a VMware cloud context so that customers can have a, a consistent experience on premises running VMware cloud running with HPE GreenLake and then two are various VMware cloud suppliers around the world. And it's not just the hyperscalers, right? There's thousands of VMware cloud, uh, you know, partners that we work with manage service providers across the board. So it's, it's a very significant network of cloud. And you know, being consistent allows for mobility of workloads allows for consistency and skill sets for it operators as well. Mm-hmm >><affirmative> yeah. I wanna get into that, um, manage service trend around skill sets, but yeah, I have a, the number one thing that we've got in our, my notes here on multi-cloud challenges and I wanna get your reaction to it real quick, inconsistent infrastructure, API database network, and security constructs are different by cloud. How do you guys view that? And when you go to customers and they say, well, I got APIs that are different. I got different security constructs. What do I do? What does that, how do you answer that, that, that, that objection. >>Well, it's, it's a great call out cuz it is still the ongoing challenge, right? To gets to some of the portability, some of unified model and how they treat resources and consumption. Right? And so we're, we've all gotten together as an industry. You'll see purposely that the hyperscalers are all here at, at the conference, right? We're working on deep integration with all of our partners to make sure the customer doesn't have to. And I think it does extend to the different security models are troubling for customers. We're all working hard on unified security models as well. It's not just a developer saying, I like this set of APIs anymore, right? Or this framework customers need to run tier zero tier one, tier three applications when it really comes down to it and we need to create that unified model together. So, and I think that's really what the, the spirit or the embodiment of hybrid really is. >>When you talk to any customer, who's running a big operation, they're running in that model, right? They're not just doing cool. They want operationally simplicity. And I think you'll see these, these things we're engineering together are going after some of the hard problems, applications are hungry or all the time customers need more and more resources. And I think we would all agree. We've spent a lot of time in industry together when we're all working on sort of systems of record. What I call the shift ride effect is happening. Now we're in systems of interaction and systems of engagement out at the edge. That's the creation point of data. We need to be able to have that unified model all the way through the data path for the customer so they can monetize business value. >>And the data model is coming together. That's right. Where all three of those types of work that's right. There's two iconic names. And the other thing is that their trusted names and you're right, you're solving some of those hard problems making it simpler, but also you people trust that if something goes wrong, you're gonna be able to recover. So guys. >>Yeah. And I, and I'll tell you on the security front, you know, we've worked closely together here. If you look at, you know, VMware strategy of intrinsic security, it's really around going back to the development of our products, making sure there's a secure bill of materials, working with these guys on route of trust. Right? Making sure there's a full stack, uh, solution for our customers. Ultimately >>That's a whole nother cube segment that's bombs and shifting left and supply chain. Absolutely >>Shifting game. Absolutely. Right. Shifting >>Lift we're >>Shifting. Right guys. Awesome story. Congrats on the collaboration. Really appreciate your time in the cube. Thank you so >>Much. Thank you so >>Much. All right. You're very welcome. Okay, John and I will be back right after this short break. You're watching the Cube's coverage of HPE discover 2022 from Las Vegas, right back.

>>Welcome back to Vegas guys, Lisa Martin and Dave Lanta here wrapping up our coverage of day two of snowflake summit. We have given you a lot of content in the last couple of days. We've had a lot of great conversations with snowflake folks with their customers and with partners. And we have an alumni back with us. Please. Welcome back to the queue. Mike Palmer, CEO of Sigma computing. Mike. It's great to see you. >>Thanks for having me. And I guess again >>Exactly. >>It's fantastic me. >>So talk to the audience about Sigma before we get into the snowflake partnership and what you guys are doing from a technical perspective, give us that overview of the vision and some of the differentiators. >>Sure. You know, you've over the last 12 years, companies have benefited from enormous investments and improvements in technology in particular, starting with cloud technologies, obviously going through companies like snowflake, but in terms of the normal user, the one that makes the business decision in the marketing department and the finance team, you know, in the works in the back room of the supply chain, doing inventory very little has changed for those people. And the time had come where the data availability, the ability to organize it, the ability to secure it was all there, but the ability to access it for those people was not. And so what Sigma's all about is taking great technology, finding the skillset they have, which happens to be spreadsheets. There are billion license spreadsheet users in the world and connecting that skillset with all of the power of the cloud. >>And how do you work with snowflake? What are some of the, the what's the joint value proposition? >>How are they as an investor? That's what I wanna know. Ah, >>Quiet, which is the way we like them. No, I'm just kidding. Snowflake is, well, first of all, investment is great, but partnership is even better. Right. You know, and I think snowflake themselves are going through some evolution, but let's start with the basics of technology where this all starts because you know, all of the rest doesn't matter if the product is not great, we work directly on snowflake. And what that means is as an end user, when I, when I sit on that marketing team and I want to understand and, and connect, how did I get a, a customer where I had a pay to add? And they showed up on my website and from my website, they went to a trial. And from there, they touched a piece of syndicated contents. All of that data sits in snowflake and I, as a marketer, understand what it means to me. >>So for the first time, I want to be able to see that data in one place. And I want to understand conversion rates. I want to understand how I can impact those conversion rates. I can make predictions. What that user is doing is going to, to Sigma accessing live data in snowflake, they're able to ask ad hoc questions, questions that were never asked questions, that they don't exist in a filter that were never prepped by a data engineer. So they could truly do something creative and novel in a very independent sort of way. And the connection with Snowflake's live data, the performance, the security and governance that we inherit. These are all facilitators to really expand that access across the enterprise. So at, at a product level, we were built by a team of people, frankly, that also were the original investors in snowflake by two amazing engineers and founders, Rob will and Jason France, they understood how snowflake worked and that shows up in the product for our end customers. >>So, but if I may just to follow up on that, I mean, you could do that without snowflake, but what, it would be harder, more expensive. Describe what you'd have to go through to accomplish that outcome. >>And I think snowflake does a good job of enabling the ecosystem at large. Right. But you know, you always appreciate seeing early access to understand what the architecture's going to look like. You know, some of the things that I will, you know, leaning forward that we've heard here that we're very excited about is snowflake going to attack the TP market, right? The transactional market, one of the transactional database market. I, yeah. Right. You know, one of the things that we see coming, and, and one of the bigger things that we'll be talking about in Sigma is not just that you can do analytics out of snowflake. I think that's something that we do exceptionally well on an ad hoc basis, but we're gonna be the first that allow you to write into snowflake and to do that with good performance. And to do that reliably, we go away from OAP, which is the terminology for data warehousing. >>And we go toward transactional databases. And in that world, understanding snowflake and working collaboratively with them creates again, a much better experience for the end customer. So they, they allow us into those programs, even coming to these conferences, we talk to folks that run the industry teams, trying to up level that message and not just talk database and, and analytics, but talk about inventory management. How do we cut down the gap that exists between POS systems and inventory ordering, right? So that we get fewer stockouts, but also that we don't overorder. So that's another benefit, >>Strong business use cases. >>That's correct. >>And you're enabling those business users to have access to that data. I presume in near real time or near real time, so that they can make decisions that drive marketing forward or finance forward or legal >>Forward. Exactly. We had a customer panel yesterday. An example of that go puff is hopefully most of the viewers are familiar with, as a delivery company. This is a complicated business to run. It's run on the fringes. When we think about how to make money at it, which means that the decisions need to be accurate. They need to be real time. You can't have a batch upload for delivery when they're people are on the street, and then there's an issue. They need to understand the exact order at that time, not in 10 minutes, not from five minutes ago, right. Then they need to understand, do I have inventory in the warehouse when the order comes in? If they don't, what's a replacement product. We had a Mike came in from go puff and walked us through all of the complexity of that and how they're using Sigma to really just shorten those decision cycles and make them more accurate. You know, that's where the business actually benefits and, >>And actually create a viable business model. Cuz you think back to the early, think back to the.com days and you had pets.com, right? They couldn't make any money. Yeah. Without chewy. Okay. They appears to be a viable business model. Right? Part of that is just the efficiencies. And it's sort of a, I dunno if those are customers that they may or may not be, but they should be if they're not >>Chewy is, but okay. You know, and that's another example, but I'll even pivot to the various REI and other retailers. What do they care about cohorts? I'm trying to understand who's buying my product. What can I sell to them next? That, that idea of again, I'm sitting in a department, that's not data engineering, that's not BI now working collaboratively where they can get addend engineer, putting data sets together. They have a BI person that can help in the analytics process. But now it's in a spreadsheet where I understand it as a marketer. So I can think about new hierarchies. I wanna know it by customer, by region, by product type. I wanna see it by all of those things. I want to be able to do that on the fly because then it creates new questions that sort of flow. If you' ever worked in development, we use the word flow constantly, right? And as people that flow is when we have a question, we get an answer that generates a question. We have, we just keep doing that iteratively. That that is where Sigma really shines for them. >>What does a company have to do to really take advantage of, of this? I, if they're kind of starting from a company that's somewhat immature, what are the sort of expectations, maybe even outta scope expectations so they can move faster, accelerate analytics, a lot of the themes that we've heard today, >>What does an immature company is actually even a question in, in and of itself? You know, I think a lot of companies consider themselves to be immature simply because for various constraint reasons, they haven't leveraged the data in the way that they thought possible. Good, >>Good, good definition. Okay. So not, not, >>Not, I use this definition for digital transformation. It very simple. It is. Do you make better decisions, faster McKenzie calls this corporate metabolism, right? Can you speed up the metabolism of, of an enterprise and for me and for the Sigma customer base, there's really not much you have to do once. You've adopted snowflake because for the first time the barriers and the silos that existed in terms of accessing data are gone. So I think the biggest barrier that customers have is curiosity. Because once you have curiosity and you have access, you can start building artifacts and assets and asking questions. Our customers are up and running in the product in hours. And I mean that literally in hours, we are a user in snowflake, that's a direct live connection. They are able to explore tables, raw. They can do joins themselves if they want to. They can obviously work with their data engineering team to, to create data sets. If that's the preferred method. And once they're there and they've ever built a pivot table, they can be working in Sigma. So our customers are getting insights in the first one to two days, you referenced some, those of us are old enough to remember pest.com. Also old enough to remember shelfware that we would buy. We are very good at showing customers that within hours they're getting value from their investment in Sigma. And that, that just creates momentum, right? Oh, >>Tremendous momentum and >>Trust and trust and expansion opportunities for Sigma. Because when you're in one of those departments, someone else says, well, you know, why do you get access to that data? But I don't, how are you doing this? Yeah. So we're, you know, I think that there's a big movement here. People, I often compare data to communication. If you go back a hundred years, our communication was not limited. As it turns out by our desire to communicate, it was limited by the infrastructure. We had the typewriter, a letter and the us postal service and a telephone that was wired. And now we have walk around here. We, everything is, is enabled for us. And we send, you know, hundreds and thousands of messages a day and probably could do more. You will find that is true. And we're seeing it in our product is true of data. If you give people access, they have 10 times as many questions as they thought they had. And that's the change that we're gonna see in business over the next few years, >>Frank Salman's first book, what he was was CEO of snowflake was rise of the data cloud. And he talked about network effects. Basically what he described was Metcalf's law. Again, go back to the.com days, right? And he, Bob Metcalf used the phone system. You know, if there's two people in the phone system, it's not that valuable, right. >>You know, exactly, >>You know, grow it. And that's where the value is. And that's what we're seeing now applied to data. >>And even more than that, I think that's a great analogy. In fact, the direct comparison to what Sigma is doing actually goes one step beyond everything that I've been talking about, which is great at the individual level, but now the finance team and the marketing team can collaborate in the platform. They can see data lineage. In fact, one of our, our big emphasis points here is to eliminate the sweet products. You know, the ones where, you know, you think you're buying something, but you really have a spreadsheet product here and a document product there and a slide product over there. And they, you know, you can do all of that in Sigma. You can write a narrative. You can real time live, edit on numbers. You, you know, if you want to, you could put a picture in it. But you know, at Sigma we present everything out of our product. Every meeting is live data. Every question is answered on the spot. And that's when, you know, you know, to your point about met cap's law. Now everybody's involved in the decision making. They're doing it real time. Your meetings are more productive. You have fewer of them because they're no action items, right. We're answering our questions there and we're, and we're moving forward. >>You know, view were meeting sounds good. Productivity is, is weird now with the, the pandemic. But you know, if you go back to the nineties here am I'm, I'm dating myself again, but that's okay. You know, you, you didn't see much productivity going on when the PC boom started in the eighties, but the nineties, it kicked in and pre pandemic, you know, productivity in the us and Europe anyway has been going down. But I feel like Mike, listen to what you just described. I, how many meetings have we been in where people are arguing about them numbers, what are the assumptions on the numbers wasting so much time? And then nothing gets done and they, then they, they bolt cut that away and you drive in productivity. So I feel like we're on a Renaissance of productivity and a lot of that's gonna be driven by, by data. Yeah. And obviously communications the whole 5g thing. We'll see how that builds out. But data is really the main spring of, I think, a new, new Renaissance in productivity. >>Well, first of all, if you could find an enterprise where you ask the question, would you rather use your data better? And they say, no, like, you know, show me, tell me that I'll short their stock immediately. But I do agree. And I, unfortunately I have a career history in that meeting that you just described where someone doesn't like, what you're showing them. And their first reaction is to say, where'd you get that data? You know, I don't trust it. You know? So they just undermined your entire argument with an invalid way of doing so. Right. When you walk into a meeting with Sigma where'd, where'd you get that data? I was like, that's the live data right now? What question do you want answer >>Lineage, right. Yeah. And you know, it's a Sen's book about, you know, gotta move faster. I mean, this is an example of just cutting through making decisions faster because you're right. Mike and the P the P and L manager in a meeting can, can kill the entire conversation, you know, throw FUD at it. Yeah. You know, protect his or her agenda. >>True. But now to be fair to the person, who's tended to do that. Part of the reason they've done that is that they haven't had access to that data before the meeting and they're getting blindsided. Right. So going back to the collaboration point. Yes. Right. The fact we're coming to this discussion more informed in and of itself takes care of some of that problem. Yeah. >>For sure. And if, and if everybody then agrees, we can move on and now talk about the really important stuff. Yeah. That's good. It >>Seems to me that Sigma is an enabler of that curiosity that you mentioned that that's been lacking. People need to be able to hire for that, but you've got a platform that's going here. You go ask >>Away. That's right in the we're very good. You know, we love being a SaaS platform. There's a lot of telemetry. We can watch what we call our mouse to Dows, you know, which is our monthly average users to our daily average users. We can see what level of user they are, what type of artifacts they build. Are they, you know, someone that creates things from scratch, are they people that tend to increment them, which by the way, is helpful to our customers because we can then advise them, Hey, here's, what's really going on. You might wanna work with this team over here. They could probably be a little better of us using the data, but look at this team over here, you know, they've originated five workbooks in the last, you know, six days they're really on it. There's, there's, you know, that ability to even train for the curiosity that you're referring to is now there, >>Where are your customer conversations? Are they at the lines of business? Are they with the chief data officer? What does that look like these days? >>Great question. So stepping back a bit, what, what is Sigma here to do? And, and our first phase is really to replace spreadsheets, right? And so one of the interesting things about the company is that there isn't a department where a spreadsheet isn't used. So Sigma has an enormous Tam, but also isn't necessarily associated with any particular department or any particular vertical. So when we tend to have conversations, it really depends on, you know, either what kind of investment are you making? A lot of mid-market companies are making best technology investments. They're on a public cloud, they're buying snowflake and they wanna understand what's, what's built to really make this work best over the next number of years. And those are very short sales for us because we, we prove that, you know, in, in minutes to hours, if you're working at a large enterprise and you have three or four other tools, you're asking a different question. >>And often you're asking a question of what I call exploration. We have a product that has dashboards and they've been working for us and we don't wanna replace the dashboard. But when we have a question about the data in the dashboard, we're stuck, how do we get to the raw data? How do we get to the example that we can actually manage? You can't manage a dashboard. You can't manage a trend line, but if you get into the data behind the trend line, you can make decisions to change business process, to change quality, accuracy, to change speed of execution. That is what we're trying to enable. Those conversations happen between the it team who runs technology and the business teams who are responsible for the decisions. So we are, you know, we have a cross departmental sale, but across every department, >>One of the things we're not talking about at this event, which is kind of interesting, cause it's all we've been talking about is the macro supply chain challenges, Ukraine, blah, blah, blah, and the stock market. But, but how are you thinking about that? Macro? The impacts you're seeing, you know, a lot of private companies being, you know, recapped, et cetera, you guys obviously very well funded. Yeah. But how do you think about, I mean, I asked Frank a similar question. He's like, look, it's a marathon. We don't worry about it. We, you know, they made the public market, they get 5 billion in cash. Yeah. Yeah. How are you thinking about it? >>You know, first of all, what's the expression, right? You never, never waste a good, you know, in this case recession, no, we don't have one yet, but the impetus is there, right. People are worried. And when they're worried, they're thinking about their bottom lines, they're thinking about where they're going to get efficiency and their costs. They're already dealing with the supply chain issues of inventory. We all have it in our personal lives. If you've ordered anything in the last six months, you're used to getting it in, you know, days to weeks. And now you're getting in months, you know, we had customers like us foods as a good example, like they're constantly trying to align inventory. They have with transportation that gets that inventory to their end customers, right? And they do that with better data accuracy at the end point, working with us on what we are launching. >>And I mentioned earlier, having more people be able to update that data creates more data, accuracy creates better decisions. We align that then with them and better collaboration with the folks that then coordinate the trucks with Prologis and the panel yesterday, they're the only commercial public company that reports their, their valuations on a quarterly basis. They work with Sigma to trim the amount of time it takes their finance team to produce that data that creates investor confidence that holds up your stock price. So I mean the, the importance of data relative to all the stakeholders in enterprise cannot be overstated. Supply chain is a great example. And yes, it's a marathon because a lot of the technology that drives supply chain is old, but you don't have to rip out those systems to put your data into snowflake, to get better access through Sigma, to enable the people in your environment to make better decisions. And that's the good news. So for me, while I agree, there's a marathon. I think that most of the, I dunno if I could continue this metaphor, but I think we could run quite far down that marathon without an awful lot of energy by just making those couple of changes. >>Awesome. Mike, this has been fantastic. Last question. I, I can tell, I know a lot of growth for Sigma. I can feel it in your energy alone. What are some of the key priorities that you're gonna be focusing on for the rest of the year? >>Our number one priority, our number two priority and number three priority are always build the best product on the market, right? We, we want customers to increase usage. We want them to be delighted. You know, we want them to be RA. Like we have customers at our booth that walk up and it's like, you're building a great company. We love your product. I, if you want to show up happy at work, have customers come up proactively and tell you how your products changed their life. And that is, that is the absolute, most important thing because the real marathon here is that enablement over the long term, right? It is being a great provider to a bunch of great companies under that. We are growing, you know, we've been tripling the company for the fast few years, every year, that takes a lot of hiring. So I would've alongside product is building a great culture with bringing the best people to the company that I guess have my energy level. >>You know, if you could get paid in energy, we would've more than tripled it, you know, but that's always gonna be number two, where we're focused on the segment side, you know, is really the large enterprise customer. At this point, we are doing a great job in the mid-market. We have customer, we have hundreds of customers in our free trial on a constant basis. I think that without wanting to seem over confident or arrogant, I think our technology speaks for itself and the product experience for those users, making a great ROI case to a large enterprise takes effort. It's a different motion. We're, we're very committed to building that motion. We're very committed to building out the partner ecosystem that has been doing that for years. And that is now coming around to the, the snowflake and all of the ecosystem changes around snowflake because they've learned these customers for decades and now have a new opportunity to bring to them. How do we enable them? That is where you're gonna see Sigma going over the next couple of years. >>Wow, fantastic. Good stuff. And a lot of momentum, Mike, thank you so much for joining Dave and me talking about Sigma, the momentum, the flywheel of what you're doing with snowflake and what you're enabling customers to achieve the massive business outcomes. Really cool stuff. >>Thank you. And thank you for continuing to give us a platform to do this and glad to be back in conferences, doing it face to face. It's fantastic. >>It it's the best. Awesome. Mike, thank you for Mike Palmer and Dave ante. I'm Lisa Martin. You've been watching the cube hopefully all day. We've been here since eight o'clock this morning, Pacific time giving you wall the wall coverage of snowflake summit 22 signing off for today. Dave and I will see you right bright and early tomorrow morning. I will take care guys.

>>Good morning live from Las Vegas, Lisa Martin and Dave Lanta here covering snowflake summit 22. Dave, it's great to be here in person. The keynote we just came from was standing room only. In fact, there was overflow. People are excited to be back and to hear from the company in person the first time, since the IPO, >>Lots of stuff, lots of deep technical dives, uh, you know, they took the high end of the pyramid and then dove down deep in the keynotes. It >>Was good. They did. And we've got Doug Hench with us to break this down in the next eight to 10 minutes, VP and principle analyst at constellation research. Doug, welcome to the cube. >>Great to be here. >>All right, so guys, I was telling Dave, as we were walking back from the keynote, this was probably the most technical keynote I've seen in a very long time. Obviously in person let's break down some of the key announcements. What were some of the things Dave that stood out to you and what they announced just in the last hour and a half alone? >>Well, I, you know, we had a leave before they did it, but the unit store piece was really interesting to me cuz you know, the big criticism is, oh, say snowflake, that doesn't do transaction data. It's just a data warehouse. And now they're sort of reaching out. We're seeing the evolution of the ecosystem. Uh, sluman said it was by design. It was one of the questions I had for them. Is this just kind of happen or is it by design? So that's one of many things that, that we can unpack. I mean the security workload, uh, the, the Apache tables, we were just talking about thatt, which not a lot of hands went up when they said, who uses Apache tables, but, but a lot of the things they're doing seem to me anyway, to be trying to counteract the narrative, that snow, I mean that data bricks is put out there about you guys. Aren't open, you're a walled garden and now they're saying, Hey, we're we're as open as anybody, but what are your thoughts, Doug? >>Well, that's the, the iceberg announcement, uh, also, uh, the announcement of, of uni store being able to reach out to, to any source. Uh, you know, I think the big theme here was this, this contrast you constantly see with snowflake between their effort to democratize and simplify and disrupt the market by bringing in a great big tent. And you saw that great big tent here today, 7,000 people, 2,007,000 plus I'm told 2000 just three years ago. So this company is growing hugely quickly, >>Unprecedented everybody. >>Yeah. Uh, fastest company to a billion in revenue is Frank Salman said in his keynote today. Um, you know, and I think that there's, there's that great big tent. And then there's the innovations they're delivering. And a lot of their announcements are way ahead of the J general availability. A lot of the things they talked about today, Python support and some, some other aspects they're just getting into public preview. And many of the things that they're announcing today are in private preview. So it could be six, 12 months be before they're generally available. So they're here educating a lot of these customers. What is iceberg? You know, they're letting them know about, Hey, we're not just the data warehouse. We're not just letting you migrate your old workloads into the cloud. We're helping you innovate with things like the data marketplace. I see the data marketplace is really crucial to a lot of the announcements they're making today. Particularly the native apps, >>You know, what was interesting sluman in his keynote said we don't use the term data mesh, cuz that means has meaning to the people, lady from Geico stood up and said, we're building a data mesh. And when you think about, you know, the, those Gemma Dani's definition of data mesh, Snowflake's actually ticking a lot of boxes. I mean, it's it's is it a decentralized architecture? You could argue that it's sort of their own wall garden, but things like data as product we heard about building data products, uh, uh, self-serve infrastructure, uh, computational governance, automated governance. So those are all principles of Gemma's data mesh. So I there's close as anybody that, that I've seen with the exception of it's all in the data cloud. >>Why do you think he was very particular in saying we're not gonna call it a data mesh? I, >>I think he's respecting the principles that have been put forth by the data mesh community generally and specifically Jamma Dani. Uh, and they don't want to, you know, they don't want to data mesh wash. I mean, I, I, I think that's a good call. >>Yeah, that's it's a little bit out there and, and it, they didn't talk about data mesh so much as Geico, uh, the keynote or mentioned their building one. So again, they have this mix of the great big tent of customers and then very forward looking very sophisticated customers. And that's who they're speaking to with some of these announcements, like the native apps and the uni store to bring transactional data, bring more data in and innovate, create new apps. And the key to the apps is that they're made available through the marketplace. Things like data sharing. That's pretty simple. A lot of, uh, of their competitors are talking about, Hey, we can data share, but they don't have the things that make it easy, like the way to distribute the data, the way to monetize the data. So now they're looking forward monetizing apps, they changed the name from the data marketplace to the, to the snowflake marketplace. So it'll be apps. It will be data. It'll be all sorts of innovative products. >>We talk about Geico, uh, JPMC is speaking at this conference, uh, and the lead technical person of their data mesh initiative. So it's like, they're some of their customers that they're putting forth. So it's kind of interesting. And then Doug, something else that you and I have talked about on the, some of the panels that we've done is you've got an application development stack, you got the database over there and then you have the data analytics stack and we've, I've said, well, those things come together. Then people have said, yeah, they have to. And this is what snowflake seems to be driving towards. >>Well with uni store, they're reaching out and trying to bring transactional data in, right? Hey, don't limit this to analytical information. And there's other ways to do that, like CDC and streaming, but they're very closely tying that again to that marketplace, with the idea of bring your data over here and you can monetize it. Don't just leave it in that transactional database. So a, another reach to a broader play across a big community that they're >>Building different than what we saw last week at Mongo, different than what you know, Oracle does with, with heat wave. A lot of ways to skin a cat. >>That was gonna be my next question to both of you is talk to me about all the announcements that we saw. And, and like we said, we didn't actually get to see the entire keynote had come back here. Where are they from a differentiation perspective in terms of the competitive market? You mentioned Doug, a lot of the announcements in either private preview or soon to be public preview early. Talk to me about your thoughts where they are from a competitive standpoint. >>Again, it's that dichotomy between their very forward looking announcements. They're just coming on with things like Python support. That's just becoming generally available. They're just introducing, uh, uh, machine learning algorithms, like time series built into the database. So in some ways they're catching up while painting this vision of future capabilities and talking about things that are in development or in private preview that won't be here for a year or two, but they're so they're out there, uh, talking about a BLE bleeding edge story yet the reality is the product sometimes are lagging behind. Yeah, >>It's interesting. I mean, they' a lot of companies choose not to announce anything until it's ready to ship. Yeah. Typically that's a technique used by the big whales to try to freeze the market, but I think it's different here. And the strategy is to educate customers on what's possible because snowflake really does have, you know, they're trying to differentiate from, Hey, we're not just a data warehouse. We have a highly differentiatable strategy from whether it's Oracle or certainly, you know, Mongo is more transactional, but, but you know, whether it's couch base or Redis or all the other databases out there, they're saying we're not a database, we're a data cloud. <laugh> right. Right. Okay. What is that? Well, look at all the things that you can do with the data cloud, but to me, the most interesting is you can actually build data products and you can monetize that. And their, the emphasis on ecosystem, you, they look at Salman's previous company would ServiceNow took a long time for them to build an ecosystem. It was a lot of SI in smaller SI and they finally kind of took off, but this is exceeding my expectations and ecosystem is critical because they can't do it all. You know, they're gonna O otherwise they're gonna spread themselves to >>That. That's what I think some competitors just don't get about snowflake. They don't get that. It's all about the community, about their network that they're building and the relationships between these customers. And that they're facilitating that with distribution, with monetization, things that are hard. So you can't just add sharing, or you can share data from one of their, uh, legacy competitors, uh, in, in somebody else's marketplace that doesn't facilitate the transaction that doesn't, you know, build on the community. Well, >>And you know, one of the criticisms too, of the criticism on snowflake goes, they don't, you know, they can't do complex joins. They don't do workload management. And I think their answer to that is, well, we're gonna look to the ecosystem to do that. Or you, you saw some kind of, um, cost governance today in the, in the keynote, we're gonna help you optimize your spend, um, a little different than workload management, but related >>Part of their governance was having a, a, a node, uh, for every workload. So workload isolation in that way, but that led to the cost problems, you know, like too many nodes with not enough optimization. So here too, you saw a lot of, uh, announcements around cost controls, budgets, new features, uh, user groups that you could bring, uh, caps and guardrails around those costs. >>In the last couple minutes, guys talk about their momentum. Franks Lutman showed a slide today that showed over 5,900 customers. I was looking at some stats, uh, in the last couple of days that showed that there is an over 1200% increase in the number of customers with a million plus ARR. Talk about their momentum, what you expect to see here. A lot of people here, people are ready to hear what they're doing in person. >>Well, I think this, the stats say it all, uh, fastest company to a, to a billion in revenue. Uh, you see the land and expand experience that many companies have and in the cost control, uh, announcements they were making, they showed the typical curve like, and he talked about it being a roller coaster, and we wanna help you level that out. Uh, so that's, uh, a matter of maturation. Uh, that's one of the downsides of this rapid growth. You know, you have customers adding new users, adding new clusters, multi clusters, and the costs get outta control. They want to help customers even that out, uh, with reporting with these budget and cost control measures. So, uh, one of the growing pains that comes with, uh, adding so many customers so quickly, and those customers adding so many users and new, uh, workloads quickly, >>I know we gotta break, but last point I'll make about the key. Uh, keynote is SL alluded to the fact that they're not taking the foot off the gas. They don't see any reason to, despite the narrative in the press, they have inherent profitability. If they want to be more profitable, they could be, but they're going for growth >>Going for growth. There is so much to unpack in the next three days. You won't wanna miss it. The Cube's wall to oil coverage, Lisa Martin for Dave Valenti, Doug hen joined us in our keynote analysis. Thanks so much for walking, watching stick around. Our first guest is up in just a few minutes.